{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "arr1 = np.random.rand(4, 4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "matrix([[0.35924302, 0.19420265, 0.49172786, 0.06097578],\n",
       "        [0.92808798, 0.51769156, 0.7877266 , 0.5068711 ],\n",
       "        [0.38811349, 0.08401502, 0.44587238, 0.65656998],\n",
       "        [0.5672154 , 0.13713185, 0.86414086, 0.43259495]])"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mat1 = np.mat(arr1)\n",
    "mat1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5068711038859587"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mat1[1,3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "matrix([[0.51769156, 0.7877266 ],\n",
       "        [0.08401502, 0.44587238]])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mat1[1:3,1:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.35924302, 0.49172786],\n",
       "       [0.38811349, 0.44587238]])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "arr1[0:3:2,0:3:2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "matrix([[-22.91781339,   7.17341183, -11.65603049,  12.51617956],\n",
       "        [ 22.74135744,  -4.54909177,  10.89917996, -14.41751271],\n",
       "        [  9.25568867,  -3.26542956,   3.64793462,  -3.01516535],\n",
       "        [  4.35176937,  -1.44073148,   4.54125944,  -3.50614818]])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mat1.I"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1., 0., 0., 0.],\n",
       "       [0., 1., 0., 0.],\n",
       "       [0., 0., 1., 0.],\n",
       "       [0., 0., 0., 1.]])"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.eye(4,4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f5a8590d900>,\n",
       " <matplotlib.lines.Line2D at 0x7f5a8590d8d0>,\n",
       " <matplotlib.lines.Line2D at 0x7f5a8590d960>,\n",
       " <matplotlib.lines.Line2D at 0x7f5a8590d990>]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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OtFDhbgiqbzah5lQXpGIRbl8YGhehWLkUX53FFe6+SUlvSHq9ugkuD8P8CYnIS1cLHQ4AYNUMLZLi5DCabdgahYW7lLyQsFR9sgtnu/uhUkpx/axMocPhzR2fiImpcehzuPHJ/mahwyHn+deX3NC/viAdWgGWR1/IbfO5u+jyg0Z0U6+gkOJ0e/BGDVeEf0fxBGGDGcKncLcm+hYJUPJCwtK7e7hal2sL0qGUCT/07yUSifCNgdbvNHUUWvodbnw8kFB+O0RGXbzyM9WYnq6Gw+3Be3vPCR0OGWJTvRFtFjtSVQqUztAJHY4Pb73U1sa2qCvcpeSFhJ1+hxuGg9z8841zhK36H8mNczIhEYuwp6kHx9osQodDBmw+3Aqrw42spBjMn5AodDg+RCIRblswmPTSarXQ8c7ALs63zc+CXBpal0xv4a6HIeo67obWO0HIKGw+3IpeuwvjEmMwb3xoXYQAIE2lxPJpaQBA29eHkPcHRjS+NiszZGqkhvrqrEwoZWI0tlpQRx13Q0JHrx1fHOsAEJo3SgBwm7dwd3d0Fe5S8kLCjnfK6MbZmYI1iroUb+Huu3vOwhlFHyihqrPXjm1HuKLG62eHTo3UUJoYGVYPrFZ7sya67qJD1cf7muH2MBRmJWCCgH2kLqZ0hhaJsTK0mKKrcJeSFxJW2iw27DjK3Ql9LUTvhABg+bRUpKoU6Oh1oOJwm9DhRL2P97dwF6FxGkxKjRc6nAu6daBw96P9zbRaLQR8MLCFhHcbh1CkkEr4TT6jqV6KkhcSVj6s4+6EZmcnCNpR91KkEjFunMPd4b+9m+6ihfbuwIf6DSE66uI1f8LgajXDgRahw4lqpzut2NvUA7EI+Eqh8M0ML8b7e13R0Bo1SS8lL2PAGKNljALz3lncGOIXIQD8qqOtjW1os9C+NUI50d6LfWd6IBGL8JWZoXsHDXCFuzcMLP3/eD8lL0L6oI4bdblqcgrSVKGzrH4kMzLUyEmJg83pQcXhVqHDCYqgJC/PPvssJkyYAKVSiaKiItTU1Fzw3JdffhkikcjnS6kU/hdnT1M3lj25Fd956cKxk8BqNFpQ32yGTBL6FyEAmJQaj1lZCfAwrn8HEcb7Axehq6ekIFWlEDiaS/vKwJYFO4910M2SQBhjeL9uYLQuhPpIXYhIJMJ1A783H+2Ljv5SAU9e3nrrLaxbtw6PPfYY9uzZg8LCQpSWlqKt7cJ1AGq1Gi0tLfzX6dPC75w5LjEGTV192HfWhDNdfUKHE5Xe3csV6i6flobEOLnA0YyO90JEd9HCYIwNrjIKg9E6gFv+Oj1dDZeHobyekl4hHDxnxol2KxRSMUrzQ6u3y4VcN1CXs+1IO0x9ToGjCbyAJy9//OMfcc899+Cuu+7C9OnT8fzzzyM2Nhb//Oc/L/g9IpEIOp2O/9JqtYEO85LSVEosmJAEADAcpAtRsLk9gxehUF2yOBL9wOqRXae60GqmqaNg29PUg6auPsTKJbhmuvCfI6PlrbH4mLo0C+KDgVGXkulaxCukAkczOlO0KuTqVHC6Gb8PUyQLaPLicDhQW1uLkpKSwRcUi1FSUoLKysoLfl9vby/Gjx+PrKwsXH/99aivr7/guXa7HWaz2ecrULw70H5yIPJ/MUJN5fFOtJrt0MTIsDw3VehwRi0zIQZzshPAGKgAUwDehLdshg6x8vC4CAHAVwq4u+jK451ot9gFjia6uD0MHw5MvYTDlNFQ3tGXj6Ig6Q1o8tLR0QG32z1s5ESr1cJoHDkBmDZtGv75z3/igw8+wKuvvgqPx4NFixbh7NmRm31t2LABGo2G/8rKyvL7z+FVlq+DSATsO9ODs900dRRM3nnca2emh8ROwGNx7UB9zieUvASVw+XhRy5CfZXR+bKTY1E4TjNQL0W/N8FUdaITbRY7EmJlWDo1fG6UAN96qY7eyE56Q261UXFxMe644w7MmjULS5cuxbvvvovU1FS88MILI56/fv16mEwm/uvMmcAtS/WZOqLRl6BxuT349BD33/srBaG9ZHEkqwu4OfNdp7phNNHUUbDsONqO7j4nUlUKLJqULHQ4Y+YtSv+I6qWCyjtat7ogPeS2A7iU8clxfNIb6SO9AX1nUlJSIJFI0Nrqu3SrtbUVOt3oiqBkMhlmz56NY8eOjXhcoVBArVb7fAXS4NRRZP9ihJLqk13o7nMiMVaGBTlJQoczZumawW0MNtLvTdB4979ana+DVBJeFyFg8LOG6qWCx+Z08ysDQ7kx3cXwU0f7IvuzJqB/0XK5HHPnzkVFRQX/mMfjQUVFBYqLi0f1HG63GwcOHEB6emjccXunjupo6ihovAXSq6aH50UIoKQ32JxuD7YM9Lsoyw+Nz46xykiIwdzxiWAM+IRGX4Ji57EOWOwupGuUmD8h/G6UgMHPmppTXWgxRe5O0wG/Eqxbtw5/+9vf8Morr+Dw4cO47777YLVacddddwEA7rjjDqxfv54//xe/+AU+/fRTnDhxAnv27MG3vvUtnD59Gt/73vcCHeqopKkGf6lp6ijwPB6GTfUDF6GC8FiyOBJ9fjpEIqD2dDeao2zreiHUnOxCT58TyXHysByt8xpcah/5BZihwDvqUjpDF7L7pl1KuiaGL2+I5KQ34MnLLbfcgieffBKPPvooZs2ahbq6OpSXl/NFvE1NTWhpGfwP3N3djXvuuQd5eXlYvXo1zGYzvvzyS0yfPj3QoY7atQV0Fx0stU3daLfYoVJKcdWkFKHDuWw6jRLzx3MfKDR1FHjei9A107WQhOlFCODqLkQibsn3OUp6A8o1ZLSudEb43igBwHWFkd+wLihj8Pfffz9Onz4Nu92O6upqFBUV8ce2bt2Kl19+mf/3U089xZ9rNBrxySefYPbs2cEIc9T0Q6aO6AMlsLyjWyV52rArnjsfTR0FBzdaN3AHHSYNxi5Eq1YOuYuO3AtRKKg5NVhbN39CotDhXBF9QTrEIkR0U9XwvhoIJE09eBcd6RXdQmJs8CJUFuYXIWAw6d3bRPVSgbT3TDfaLHaoFNKwXGV0vq8MFGBSl+bA2jRktC5ca+u8UuIV/HTpp4cic6+j8H6HBORd/kp30YGz/6wJ53r6ESuXhF2/hZGkqWmpfTB4p4xW5qWFXU+gkZTN4JLe/WdNEV2AKSSf2roIuFECuAUOAPBphHbbpeTlMukH5qL3NvVQAWaAeJe6Lp+WBqUs/C9CwODUEW0xERiMDe4HFCkXoVSVAnOzuWmMLRF6Fy20/edMMJptiJNLsCiMa+uG8m6HsetUF7oicINPSl4uk1at5Ht3GGjHYL9jjPGdRSPlIgQM3g3tPdNDbd8DoL7ZjDNd/VDKxFgSAaN1Xt4LUaROAQjNO1q3PDdybpSykmIxPV0NDwMqDkfe7w0lL1fA2z9i8yFKXvytwWjBqc4+yKViLM9NEzocv9FplJg5TgMWoR8oQvPWSC2bmhZWexldyqqB1S+Vxzth6o/8HYODaWhtXbivMjrfqhmRm/RS8nIFrsnzDst1o6cv8oblhOQdzVoyJTVsdnUdLe/vzeYI/EARmvcOOpJG6wAgJyUOk9Pi4fIwbG1sEzqciHK0rRcnO6yQSyLrRgkYHOndcbQd/Q63wNH4FyUvVyA7ORbTtCq4PQyf0weKX3mnjPQRdhECgGsG7oa+ONaBPodL4Ggix7G2Xhxt64VMIoq4ixAArKKpo4DwrjK6ekpKxN0o5aWrMC4xBjanB9uPtgsdjl9R8nKFvHPRdBftP6c6rDjS2gupWISSPO2lvyHMTNOqkJUUA7vLg+1HOoQOJ2J4h/4XTUqBJkYmcDT+55062tbYDrsrsu6ihVQeoVNGACASiYasOoqsaxQlL1eoZCB5oQ8U//F2uSyamARNbORdhEQiEa7J4z5QKOn1H++UUSSO1gHAzEwN0lQK9NpdqDzeKXQ4EeFMVx/qm80QiwY/yyONt+6loqEVLrdH4Gj8h5KXK+T9QLE63PSB4ife5CUSR128vCN2n0XYB4pQjCYbDpwzQSQCVkbo741YLKKRXj/zjtYtyElCUpxc4GgCY974RCTGytDT58SuU91Ch+M3lLxcIbFYxH9Y0gfKlTMN+QOL5ORl/oREJMTK0N3nRO3pyPlAEUpFA/e3NzsrAakqhcDRBM7Q5MXjYQJHE/689UOROGXkJZWI+WvUpxG0MpaSFz/wFtJtOdwKxugD5UpsPdIGt4cN1IXECh1OwEglYqyYxhWVUtJ75SoOcwXzkTrq4lU8KRnxCinaLHbsP2cSOpyw1tPn4G8cIvlGCRhS7F0fOdcoSl78oHhSMmLlErSa7ThAHyhXxHshX5kXeatFzsffRVPSe0X6HC58cYwrfI70i5BCKsHSaVzzvUht+x4sWxvbo+JGCQCunpIKpUyMcz39ONRiFjocv6DkxQ+UMgmWTOE+UKh99+VzuDzY1sgt54vU4rmhlkxNhVwqxunOPhxt6xU6nLD1xdEOOFwejEuMwVRtvNDhBBwtmfYPb21dNNwoxQzZH25ThKw6ouTFT6h995XbdaoLFrsLKfFyzBqXIHQ4ARenkOKqgV2Paero8nmnjErytBCJRAJHE3jLc9Mgk4hwrK0XJ9op6b0cTrcH245wN0qRPtXodc3AkulI6exNyYufLM9Ng1jEtbU/09UndDhhyXsBX5GbBrE48i9CwOAHCiW9l8fjYahoGExeooFaKcPCiVzSuyVCLkTBtutkFyw2F5Lj5JiVlSB0OEGxbFoqRCJu/y+jySZ0OFeMkhc/SYqTY96EJAD0gXI5GGP8ipFouQgBQMnAkPW+Mz1oNYf/B0qw7Tvbg45eO1QKKRbkJAkdTtB4/0a8o05kbLYM/HdbnpsGSZTcKKXEKzB7IFH7rCH8f28oefEj7541lLyM3ZHWXpzp6odcKsbiKZGxJf1opKmV/J3f5xHwgRJs3ou3t34oWqwY2P5g9+lumPpoo8ax8L1Rivx6l6FW8klv+F+jouevPQi8dS/VJ7po59cx8iZ8iyenRNRuwKPh/QCtoORlzKKp6HKorKRYTNXGw+1h2BZhe9YE2vH2Xpzu7INcIsbVAwstooU36f3iWEfYb9RIyYsfTUiJw6TUOLg8DDvoA2VMovUiBAArcgc2ajzaAZszvD9Qgulsdx8ajBaIRcDyadH7e/NZBNxFB5N3tG7hpGTERdhGjJeSq1MhM4HbV63yRHjvq0bJi595h+U+o7noUWu32FF3pgcAsDI3eupdvPLSVUjXKNHvdKPyBG0xMVrei9C88UlIjNDW7hfjTfS3HmmnLSbGYHB1WvQlvCKRiB992RLm1yhKXvzM+4vxeSPXKZZc2ucNbWAMKMjUQKdRCh1O0IlEIiwf+L2hpHf0onm0DuC2QkgY2LNm70DyTy6u2+rA7tNdAAY/q6PNirzBz5pwbo5JyYufzR2fCLVSiu4+J+rO0J41oxHtFyEAWOlNXhrC+wMlWHrtLlSf4C5C0dKn43xSiRjLBhqP0SKB0dl6pA0exk2fjEuM7K66F1I8MRkxMgmMZhvqm8O32y4lL34mk4ixdNrghYhcnN3ljprW7hezaFIKFFKufXdjq0XocELejiPtcLg9yBmoM4tWK2iaeky28HtgRe+NklIm4Vd0hvM1ipKXAPDeRVMPhkurPtGFPocbWrUCMzLUQocjmBi5BFdN5j5Q6Pfm0rwrs1bkpkVFV90LWTo1FRKxCEfbetHUSc0xL8bh8mB7Y3R11b2QSFjhSMlLACydmsp32z3X0y90OCHNm/kvnxbdFyFgcA4+nO+GgsHjYdjaOHAHHaV1C16aGBnmT0gEAHzWQFNHF7M7yrYfuRjv6rx9Z3rQZgnP5piUvARAYpwcc7K9Hyh0IbqQoc2iorV4bijvf4M9Td3osjoEjiZ07T9nQkevAyqFlO9qHc28K/TC+S46GCqG3ChFy/YjF5KmVmLmOA0AYGtDeLb1oOQlQAYruulu6EKOtw921fVOmUSzjIQY5KWrwRj4kQUynPdvKtq66l6I97Om+kQXeu0ugaMJXZ8NmWokQ5Pe8LxGBeUv/9lnn8WECROgVCpRVFSEmpqai57/zjvvIDc3F0qlEgUFBdi4cWMwwvQr7y/Gl8c7w76TYaDwzaImRl+zqAvh66XoLvqC+DtouggBACamxGFCciwcbg++OBrejccC5UR7L052WCGTiKJq+5GL8RYt7wjT5pgBT17eeustrFu3Do899hj27NmDwsJClJaWoq1t5A/nL7/8Erfddhvuvvtu7N27FzfccANuuOEGHDx4MNCh+tVUbTzfyfDL4/SBMhLvRSja6xaG8t5Fb29sh5Majw1jNHHLO0Uibpdc4m08NrDqKEzvogPNO+pSlJMMlVImcDShYUaGGlq1An0ON6rCsDlmwJOXP/7xj7jnnntw1113Yfr06Xj++ecRGxuLf/7znyOe/+c//xllZWX48Y9/jLy8PPzyl7/EnDlz8MwzzwQ6VL8SiUR8Zkt30cOZ+pyoPc31waFh3EGF4xKQHCeHxe7CrlNdQocTcj4fmE6blZWAlHiFwNGEDu9nzWcN7fBQc8xhPqPRumGGdtsNx01hA5q8OBwO1NbWoqSkZPAFxWKUlJSgsrJyxO+prKz0OR8ASktLL3i+3W6H2Wz2+QoVK3Ijo5NhIGw72g63h2GqNh5ZSdHZLGokErEIy6ZRt90L8U41rojCvYwuZv6EJMQrpOjotePAOZPQ4YQUs82JmpMDDQ0pefHBj9g1ht81KqDJS0dHB9xuN7Ra3zX1Wq0WRqNxxO8xGo1jOn/Dhg3QaDT8V1ZWln+C94OFQzoZHmoJnaQqFHiLLulOaDgasRuZzenGzoGGhiuiuMnYSORSMZZMHegTRL83Pr442gGXh2FiahwmpERvQ8ORXDU5GXKpGGe6+nGsrVfocMYk7Ev1169fD5PJxH+dOXNG6JB4Stlg4zG6ix7k9jBsPTLQLCoKN2K8lKunpEAqFuFkhxUn2sPrAyWQqk50ot/phk6txPT06G1oeCFU9zIyGq27sFi5FIsmJQMIv6Q3oMlLSkoKJBIJWlt9/5haW1uh0+lG/B6dTjem8xUKBdRqtc9XKKG76OH2NnWjp88JTYwMc7IThA4n5KiUMhRN5PqXUJ+gQUPrFqK9oeFIlk1LhUgEHDxnhtEUno3H/G1oQ0MarRvZyjDdFDagyYtcLsfcuXNRUVHBP+bxeFBRUYHi4uIRv6e4uNjnfADYvHnzBc8Pdd66l31ne9BusQscTWjwJnJLp6ZCKgn7wb+AGLyLDq8PlEBhjPH/LahuYWQp8QrMykoAMFjYHO32ne1Bp5VraDifGhqOyDt1v/t0F3r6wqc5ZsCvHOvWrcPf/vY3vPLKKzh8+DDuu+8+WK1W3HXXXQCAO+64A+vXr+fPf/DBB1FeXo4//OEPaGhowP/93/9h9+7duP/++wMdakBo1UoUZGrAGH2geHkr26N5c7RL8V6ga052wWxzChyN8I629eJsdz8U1NDwomhfNV/ehHfJ1FTI6EZpROMSYzFNq4KHAduOhE+33YC/m7fccguefPJJPProo5g1axbq6upQXl7OF+U2NTWhpaWFP3/RokV4/fXX8eKLL6KwsBD/+c9/8P777yM/Pz/QoQbMijAdlguEs919aDBaIBZxIy9kZBNS4jAxNQ4uD8OOI9QnyHsxLp6UjBi5ROBoQpd3xG7nsfBsPOZvfL0LjdZdlHdKLZyS3qCkovfffz9Onz4Nu92O6upqFBUV8ce2bt2Kl19+2ef8m2++GY2NjbDb7Th48CBWr14djDADZrCTYTvsruj+QPHeCc0dn4iEWLnA0YS2krzwbt/tT5/TlNGo5KWrkK5Rot/pRmUYNh7zJ6OJW+VJDQ0vzft3te1IO1xh0hyTxtGCID9DgzSVAlaHG9Unorvx2JbD3ikjWmV0Kd67xa2NXE+caNVtdWD3ae7vhpbWX9zQxmPRPtLrvVGalZWAZGpoeFGzsxORECuDqd+JPU09QoczKpS8BIFYPOQDJYoLMHvtLlQd5+4GS6je5ZLmjk+EWilFl9WBujPdQocjmK1H2uBhQK5OhXGJ1NDwUga77YZf4zF/8i4Zp9G6S5OIRVg+zbsyNjxGeil5CZIVuYO/GNH6gfLF0XY43B6MT47FpNR4ocMJeTKJGEunhd9ctL95R+tKaLRuVBZNSoFSJsa5nn40tlqEDkcQ/Q43vvA2NKReUqOyPMxG7Ch5CZLFU1L4ToZHw6yTob/wU0a5WurTMUoro3zEzuHyYFvjQENDGq0bFaVMgkWTBrrthsmFyN+4gmUPMhNikJeuEjqcsLB0SiokYhGOtvWiqbNP6HAuiZKXIPHpZBiFHyhuD+OLLmnKaPSWTk2FWAQ0GC042x36Hyj+VnOyC712F1LiFSgclyB0OGEj2qepvVMfK/OooeFoaWJlmDc+EUB4dGmm5CWIBu+iQ/8Xw9/qzgw0i1JKMT+HmkWNVmKcHPPGc/+9wnHn1yu1ZWAPrBW5qRCL6SI0Wt7kZU9TN7qs4dN4zB88HkZTjZcpnDrCU/ISRN45xdrT3eiOsg+UioGL0FJqFjVmK8LoA8WfGGND7qDpIjQWGQkxyEtXc80xo+z35sA5E9otdsQrpPw2G2R0vH9nVSc6Q745Jl1FgmhcYixydVwnw61HousDpYLuhC6bd8Tuy+Od6HO4BI4meI629eJMVz/kUjGunkJddcdqZW54rR7xF+9o3ZKpKVBIqaHhWExKjcfElDg43QzbQ7zbLiUvQeYdltsSRXUvZ7r60NhqgUQsomZRl2FyWjyykmLgcHnwxdHo6ba7+RB3EbpqUjJi5VKBowk/10znbhS2NUZXc0yaMroy3t8b799fqKLkJci8y/a2N7bDGSadDK8UddW9MiKRCCtzw+MDxZ+8U400ZXR5CjI10Kq55phfHo+Obrtnu/twuMUMsQh83xIyNiUDycvnDW0hfY2i5CXIZmUlIDlODovdFTXddr3DuLTK6PKtmuHdKqAtKrrtdvTasfdMDwBaIn25xGIRP/oQLUmvd3p63vgkJMbRjdLlmJOdiKQ4Ocw2F3adDN1rFCUvQSYRi/gP482HjAJHE3i9Q5I0uoO+fAsmJEETI0OX1YHa05HfbffzhjYwBszIUCNdEyN0OGHLOwWw5VArPFGQ9G45PLhEmlweyZCO8JsPh27SS8mLAEpn6AAAnx6K/G67O45wXXVzUuKoq+4VkErEfAHmp/WRn/RuoSkjvyielIx4hRRtFjv2nzMJHU5AWWxOVA1sRumd+iCXZ2jdS6heoyh5EcBVk1MQK5egxWTDwXNmocMJqMGuunQndKX4D5TDofuB4g82pxs7BgqTaarxyiikEiydyhXJR/pI746jHXC6GSbSjdIVu3pKChRSMc52h+4WE5S8CEApG/xA+TSCP1Bcbg+/TJPuhK7ckqmpkEvFON3ZhyOtkbvFRNWJTvQ53NCqFcjP0AgdTtgLl9UjV2rLIZoy8pdYuRSLJ3PtCTbXh+bvDSUvAvEWYH4aor8Y/lBzsgs9fU4kxckxfwI1i7pScYrBD5RInjryXmRX5Gqpq64fLJ+WBolYhCOtvTjdaRU6nIBwuT34vJGWSPsTXy8VonUvlLwIZMU0LSRiERpbLTjVEZkfKOUDF9hr8riflVy5VUOmjiKR28OwaSChL51BFyF/0MTKUDSwJUekjr7saepBd58TmhgZ5g7sz0OuzIq8NIhEwL6zJrSabUKHMwwlLwLRxMqwcKB1dSROHXk8jB9VKsvXCRxN5FiZp4VIBOw/a0KLqV/ocPxub1M3OnrtUCml/M7I5Mp576I/jdDkpfwg9xm6MjcNUtp+xC/SVErMykoAEJqjL/QuC2jV9IFVRxE4dbTvbA+MZhviFVIsmpwsdDgRI1WlwJxs7s5ySwReiAwDF6GSPC3kUvp48hdv8rL7VFfEbdTIGEP5wRYAdKPkb6HcJ4g+HQTk/UCpbepGu8UucDT+5Z0yWp6bRvuL+Fmk3kVzFyHu98bbToD4x7jEWExPV8PDBjteR4p9Z01oNtkQK5dgyVTafsSfvNPUXx7rhNUeWvuqUfIioIyEGBRkasDYYCv0SMAYwyb+IkR1C/7m/UCpPN4JU39o7/w6FvXNZpzr6UfMkNV4xH8GVx1F1jS1YWDUZXluGpQyulHyp8lp8RifHAuH24OtjaG1USMlLwJbFYF30Udae3Gqsw9yqRjLaH8Rv5uYGo9JqXFweRi2NkbOXbT3IrRsWipi5HQR8jdv8rL9SAdszsjYqHHoaJ2epoz8TiQS8VNxGw+0CByNL0peBFY68IvxxbEO9IbYsNzl2jQwZbRkSgriFbQbcCCsGtKlOVJ4L0JUtxAYMzLUyEyIQb/THXJ30ZfrcIsFpzv7oJCKaSPGALm2IB0AN93Y7widpJeSF4FNSYvHhORYOFwebD8SGR8o3ovQKqpbCBjviN3WhraIuIs+1mbB8XYrZBIRllM35oAQiUT4ykzuQvRJiN1FXy5voe6SqamIoxulgCjI1GBcIpf0fh5CI72UvAhMJBLxF3nvRT+cnenqw6EWMyRDdrQl/lc4LgEZGiWsDndETB0ZDnC/+4snp0CtlAkcTeS6diB5qTjcGlJ30ZfLQFNGAScSifjRl1BKeil5CQHelRWR8IHinTIqyklCEm1JHzBisYi/EH20P3Q+UC6Xd3UaTRkFVkGmBllJMehzhNZd9OU41taLo229kElEtIFngK32Th0dDp2pI0peQsCc7ARkJsTAGgEfKLTUNXi+MjMDAPeB0ucI33qpM119qG82Qyyi1u6BJhKJ+AvRJ2Ge9HqnjBZNSoEmhkbrAmnmuMGpo1AZ6Q1o8tLV1YXbb78darUaCQkJuPvuu9Hbe/EN5ZYtWwaRSOTz9YMf/CCQYQpOJBLhK4UDd9H7mgWO5vK1WWyobeoGMLh3EwmcmeM0yE6KRb/TjYrDofGBcjkGR+uSkRyvEDiayPeVAi7prWhoDeukl6aMgscn6Q2RqaOAJi+333476uvrsXnzZnz88cfYvn077r333kt+3z333IOWlhb+64knnghkmCHhOu9ddEMbLLbw7N1hOGAEY8CsrASka2KEDifiiUSDU0cf7w/fpNdAq4yCKj9TjeykWNicnrBtWNfUOThadw3tWB8Uq4esOgqFRQIBS14OHz6M8vJy/P3vf0dRUREWL16Mp59+Gm+++Saamy/+QRsbGwudTsd/qdXqQIUZMmZkqDExJQ52lyck95EYjffrzgEAvlqYIXAk0cOb9H7e2B6WSW+LqR97aLQuqIYmveE6dVRez8VNo3XBUzhOg8wErl4qFKaOApa8VFZWIiEhAfPmzeMfKykpgVgsRnV19UW/97XXXkNKSgry8/Oxfv169PX1XfBcu90Os9ns8xWOuKkj7kL00b7w+0A53WnF3qYeiEXgp8BI4OWlqzAxNQ6OME16P6xrBmPAgglJNFoXREN7d4Ra2/fR2DiwOk1fQKN1wcJNHXH/vT85IPzK2IAlL0ajEWlpvv0apFIpkpKSYDRe+Af/5je/iVdffRWff/451q9fj3//+9/41re+dcHzN2zYAI1Gw39lZWX57WcItusG7oa2H2lHT194bZ72QR03mnbV5BSkqZQCRxM9uN4dXNL7cRgmve/t5UbrbpidKXAk0WVGhhoTkmNhd3lQEWZTR6c6rKg7w90oldHCgKDyTh1VHG4VfOpozMnLI488Mqyg9vyvhoaGyw7o3nvvRWlpKQoKCnD77bfjX//6F9577z0cP358xPPXr18Pk8nEf505c+ayX1toU7Qq5OpUcHlYWPV8YYzxU0bXz6KLULDxSe/Rdpj6wmfq6HCLGQ1GC+QSMT8SQILDd+oovOqlvAnvVZNTkKamG6VgmpWVMGTqSNimqmNOXh5++GEcPnz4ol8TJ06ETqdDW5tvRu9yudDV1QWdbvTZclFREQDg2LFjIx5XKBRQq9U+X+HsOu/UURh9oBw8Z8aJdisUUjFtxCiAKVoVpmlVcLoZNoXRpnvehHd5bio0sbTUNdiuLRislwqXrUkYY3zyctOccQJHE32GTh0JvdfRmJOX1NRU5ObmXvRLLpejuLgYPT09qK2t5b/3s88+g8fj4ROS0airqwMApKdHx52ZtwCz8ngn2iw2gaMZHe9FqGS6FirqjiqIr/CrjsJj6sjjYfhgL5egf42mjASRl67CxBSuXipcdrWvPd2Npq4+xMolVOAtkKGrjhwuj2BxBKzmJS8vD2VlZbjnnntQU1ODnTt34v7778ett96KjAzuAn3u3Dnk5uaipqYGAHD8+HH88pe/RG1tLU6dOoUPP/wQd9xxB5YsWYKZM2cGKtSQkp0ci8KsBHjYYMv0UOb2ML43zQ00ZSQYb7H3zmMd6LKGfr1U1clOGM02qJVS2nlcIEOnjt4fGM0Ide8OxKnPT0esnPYyEsKsrAT88oZ8bHpoCeRS4frcBvSVX3vtNeTm5mLlypVYvXo1Fi9ejBdffJE/7nQ60djYyK8mksvl2LJlC1atWoXc3Fw8/PDDuOmmm/DRRx8FMsyQ461hCIeGdVUnOtFmsUMTI8PSqalChxO1clLiMCNDDbeHCT6cOxrei+W1M9OhlEkEjiZ6eQultx1ph9EU2iO9NqcbHw98Jt44h26UhCISifDtheORmSDs6sCApq5JSUl4/fXXL3h8woQJYIzx/87KysK2bdsCGVJY+MrMDPx642HsPt2Ncz39gv+SXIz3IrS6IF3QLJxwI1/1zWa8s/sMvrVwvNDhXJDN6eZHFWm0TliTUuMxf0Iidp3qxn/3nMWa5ZOFDumCPm9og9nmgk6txMKJyUKHQwRGV5sQpNMoUZSTBAB4Z3forp6yOd38qqgbZlFjOqHdOCcTMokI+86acKg5dPsdVRxug8XuQmZCDOZPSBI6nKj3jXlce4l3dp/xuZkMNe8OWVYvEYsEjoYIjZKXEHXbgmwAwFu7zsDtCc0PlM8auItQhkZJF6EQkByvwKrp3EqAt3Y1CRzNhXlXi1w/KwNiuggJbnVBOuLkEpzq7EP1yS6hwxlRl9WBzwf60dCUEQEoeQlZpTN0SIiVocVkw7YjodlEyjtl9NVZmXQRChG3zOfuot/be07wJlIj6bI6+NbitMooNMQppHyLhrdDdKT34/3NcHkY8jPVmKpVCR0OCQGUvIQopUzC9zF4vTr0PlCMJhvfmZMuQqFj8eQUZCbEwGxzwXAw9Ap3PznQApeHYUaGGlPoIhQybh6YOtp4oAXmENwj6797uBulr82m3i6EQ8lLCLttAfeB8llDa8itBHi9pgluD8OCCUmYpqOLUKgQi0X86MubNaGV9DLG8EY1N51FCW9omZOdgMlp8bA5PSG3zcTx9l7sO9MDiVhEm74SHiUvIWxymgoLcpLgYVztS6hwuDx4o4a7CH27OHRXtUSrm+eNg1gEVJ/swon2XqHD4e0+3Y1DLWYoZWJ8fS7dQYcSkUiEWwZGX94Ksamjtwc++5ZMSUGqinaQJhxKXkLcN/nC3aaQKdwtrzei3WJHqkqBUtoYLeSka2L4xm+hdCF6eecpANyoS0KsXNhgyDBfm5MJqViEfWd60Gi0CB0OAMBqd/E3SqG8/J8EHyUvIa4snyvcbTbZsP2IsBthef278hQALrGi3i6hyTt19N/as3C6hWvh7dVi6kd5Pbes/s5FE4QNhowoJV6BlXlc0hsqhbvv7jkLs82FCcmxWE6dmMkQdOUJcT6FuzXCL3893GLGrlPdkIpF+GZRttDhkAtYkZuGVJUCHb0OVBwWfrXaq1Wn4fYwLJyYhFxdeG+eGsm8PV/e23sOdpewq9U8HoaXBkbr7roqh1Y0Eh+UvISBwcLdNsELd/9VeRoAt5RbS9vRhyyZZLCu5E2Be77YnG68MVA8/B0adQlpS6emQqtWoMvqwId1wm5Psu1IO050WKFSSqlGigxDyUsYmJymwoIJSXB7mKDDuaZ+J9/bhQp1Q5+3AHPbkXYcaxOucPejfc3osjqQmRCDkjzaCTiUSSVi3HVVDgDguW3HBa2z++fOkwCAW+dnIU5BmzASX5S8hInbirgL0atVpwVrPvaf2rPod7oxTavity8goWtCShxWTdeCMeCvnx8TJAbGGF7+8hQAruBSKqGPnFB3e1E21EopTrRb8Wm9MDvbH2m1YMfRDohFwB3FEwSJgYQ2+iQJE9cWZCBDo0Sbxc5X3weTx8PwahU3ZfTt4vEQiWj+ORw8sGIKAOCDfc043WkN+uvXnu5GfbMZCqkYtw4UEZPQplLK+KLqv249Lsh+Ry8NjLqUztAhKyk26K9PQh8lL2FCLhVjzQpux9fnth4P+ujLtqPtONlhhUohpQZjYaRgnAbLpqXC7WH46+fHg/76Lw2MutwwKxOJcbQ8OlzcdVUOYmQSHDhnwo6jHUF97S6rA+8OdNT97uKcoL42CR+UvISRm+dmITMhBm0WO16vDt7oi8fD8OSmRgDcElyafw4v3tGX/+45i7PdfUF73bPdffyu47Q8Orwkxcn5zWGfDfKU4xs1TbC7PMjPVGPe+MSgvjYJH5S8hBG5VIw1ywdGX7YFb/Tl4wMtqG82I14hxQ8HXp+Ej7njE3HV5GS4PAwvbDsRtNd9clMj3B6GqyYnY3oGLY8ON/csyYFMIkL1yS7Ung7ObtP9DjdeGRit++5VOTQ9TS6Ikpcw8/W545CZEIP2II2+OFweftTl+0smIomG/sPS/cu50Ze3dp9Bqznwy+33nenB+wNLbdfr8wL+esT/0jUxuHFgI8RgTTm+sP042ix2ZCbE4NqZ6UF5TRKeKHkJM8EefXmjpglNXX1IiVfg7qtp/jlcLZyYhPkTEuFweQI++sIYw683HgYA3Dg7E/mZmoC+HgmcHyybBLEIqGhow+EWc0Bfq7mnH89v45Kk9atzoZBKAvp6JLxR8hKGho6+vBbA0Zdeuwt/qTgKAFhbMgWxcqp1CVcikYivfXm95jQ6eu0Be63Nh1pRc7ILCqkYPyqdFrDXIYGXkxIHfQE3AvLnLUcD+lq/K2+AzenBgglJuLaARl3IxVHyEobkUjHuH1h59HwAR1/+vuMEOq0O5KTE8XvlkPB19ZQUFGYlwOb04E9bjgTkNZxuD35raAAAfO/qHGQkxATkdUjwPLBiMiRiEcrrjQHr+1J7ugsf1DVDJAIevW461bqQS6LkJUzdNGdw9OVPAbgjarfY8bft3PTCj1ZNg4yai4U9kUiEnw6MhLxa1YSdx/y/BPb16iac6LAiOU6OHyyd5PfnJ8GXq1PjnqsnAgD+3/sHYep3+vX5PR6Gxz86BAC4ee44mmYko0JXpDAll4rx869MB8AVuVUe7/Tr8z/92VFYHW4UjtNgdYHOr89NhLNocgq+vZDb2uHH7+yD2ea/C5HZ5uRHdNZeMxUqpcxvz02EtbZkCiamxKHNYsevPznk1+d+d+857D9rQrxCStOMZNQoeQljZfk63DIvC4wB696ug6nPPxeizxva8O+Bbro/LculIdwI84g+F+OTY9FssuGXH/nvQvTU5iPo7nNiUmocbqNpxoiilEnwu6/PhEgEvL37LHYcbffL81rtLjxRzk0z3r9iMtJUtNkrGR1KXsLco9dNx4TkWLSYbPjf9w5ccSvvUx1W/M+be8EY8M2ibCyanOKnSEmoiFNI8eTNhRCJgHdqz2LLodYrfs5395zFSztPAQD+37XTaQ+jCDR/QhLuGBi1e+S/B2C1u67o+RhjePyjerRZ7BifHIu7rprghyhJtKBPmDAXp5Diz7fOhlQswicHWvDfgbbal6PX7sK9/94Ni82FueMT8X/XzfBjpCSUzJ+QxNcxPPLuAXRbHZf9XLtPdeGR/x4AANy3bBKW56b5JUYSen5SlovMhBic6+nnR0wu158rjuLt3WchFgG/uD6flkaTMaHkJQIUZiXgoWumAgAe++DgZW3AxxjDj9/ZhyOtvUhTKfDc7XMgl9KvRyRbd81UTEmLR0evHT97/wA8nrGP2jV19uHef9fC4fagdIYWP15FNQuRLE4hxYYbCwAAr1Sexnt7z17W87xZ08QvNPjF9flYOjXVbzGS6EBXpwjxg6WTsGBCEqwON77/71qc6RrbHjZ/3XochoNGyCQiPPetOUhT09xzpFPKJPjjN2ZBIhZh4wEjfvjaHvQ5Rj8VYLY5cfcru9BldSA/U42nbpkFsZjqoyLdkqmpuKOYmz566K19eGHb2Haerjjcip+9fxAAcP/yyfjWwFQUIWMRsOTl17/+NRYtWoTY2FgkJCSM6nsYY3j00UeRnp6OmJgYlJSU4OjRwDZGihQSsQhP3ToLyXFyNBgtuPYvO7B5FLUMTrcHf9t+Ak9+ym0B8PhX8zF3fFKgwyUhomCcBk/ePBNyiRjl9UZ8/blKNPf0X/L7eu0uPPD6Xhxt64VWrcDf75hPTQyjyP9dNwP3DHTc3mBowC8+PjSqkbu9Td1Y8/oeuD0MN80Zh4dXTQ10qCRCBSx5cTgcuPnmm3HfffeN+nueeOIJ/OUvf8Hzzz+P6upqxMXFobS0FDZb4PdiiQSZCTH46IHFmJ2dALPNhXv+tRsbNh6G0+0Z8fzK45249i878OuNh8EYcNuCbHyzKDvIUROhfW32OLx+TxFS4uU41GLGV5/ZidrT3SOea3e58c8vTmLpE59j25F2KGVi/P2O+dBpaKQumojFIvzs2un4f9dy+1a9tPMUHnhzL+yukRtmGk02bNh4GN/6ezVsTg+WTk3Fb28qoJWM5LKJ2JUuT7mEl19+GWvXrkVPT89Fz2OMISMjAw8//DB+9KMfAQBMJhO0Wi1efvll3HrrraN6PbPZDI1GA5PJBLU6Oneydbi4Lqf/3HkSADAnOwEr87RIjpMjOV4BtVKKV6ub8NE+buO8xFgZflqWi2/My6Jh/yh2trsP9/yrFodbzJBLxCjN12FiShwmpsZhUmo8DrWY8ectR3FuYGRmQnIsfv21AlxFK9Ki2gd15/Cjd/bB6WZIVSkwb3wi5mQnYs74BChlEry08xQ+qDsHp5u71Mwbn4hXvrsAcQoaqSO+xnL9Dpnk5cSJE5g0aRL27t2LWbNm8Y8vXboUs2bNwp///OcRv89ut8NuH9ynxWw2IysrK6qTFy/DgRb85D/7YbnAkkaxCLi9aDweXjUVCbG0WzTh+m6se7sOm+ovPOWoVSvw4MqpuHneOOq8TAAAO4914Iev7blo990FOUn4/pKJWD4tjW6SyIjGkryETOprNHJ7Zmi1Wp/HtVotf2wkGzZswOOPPx7Q2MKVviAdMzI0eGt3E9rMdnRaHdxXrx05KXH4aVkuteImPuIUUjx3+1x8cawDh1vMONFuxfH2XpzosEIiFuGeq3NwR/EEKGW0rJUMumpyCqrWr8T+sz3Y09SD2tPd2NvUja4+B8pm6HDvkomYnZ0odJgkgowpeXnkkUfwu9/97qLnHD58GLm5uVcU1FisX78e69at4//tHXkhnOzkWPy4NHjvBwl/YrEIS6amYgktXyVjECOXoGhiMoomJgPgSgGcbkYtF0hAjCl5efjhh/Gd73znoudMnDjxsgLR6bj9c1pbW5GePrgdemtrq8800vkUCgUUCsVlvSYhhJDAEIlEkEtpeogExpiSl9TUVKSmBuZuLCcnBzqdDhUVFXyyYjabUV1dPaYVS4QQQgiJbAEbz2tqakJdXR2amprgdrtRV1eHuro69Pb28ufk5ubivffeA8Bl6WvXrsWvfvUrfPjhhzhw4ADuuOMOZGRk4IYbbghUmIQQQggJMwEr2H300Ufxyiuv8P+ePXs2AODzzz/HsmXLAACNjY0wmUz8OT/5yU9gtVpx7733oqenB4sXL0Z5eTmUSuohQQghhBBOwJdKBxv1eSGEEELCT1gulfYXby5mNpsFjoQQQggho+W9bo9mTCXikheLxQIAtFyaEEIICUMWiwUazcV7kEXctJHH40FzczNUKpXf983w9pA5c+ZMRE5JRfrPB0T+z0g/X/iL9J+Rfr7wF6ifkTEGi8WCjIwMiMUXX08UcSMvYrEY48aNC+hrqNXqiP2lBCL/5wMi/2ekny/8RfrPSD9f+AvEz3ipERcvan1ICCGEkLBCyQshhBBCwgolL2OgUCjw2GOPRex2BJH+8wGR/zPSzxf+Iv1npJ8v/IXCzxhxBbuEEEIIiWw08kIIIYSQsELJCyGEEELCCiUvhBBCCAkrlLwQQgghJKxQ8jLEr3/9ayxatAixsbFISEgY8ZympiZce+21iI2NRVpaGn784x/D5XJd9Hm7urpw++23Q61WIyEhAXfffTd6e3sD8BOMzdatWyESiUb82rVr1wW/b9myZcPO/8EPfhDEyEdvwoQJw2L97W9/e9HvsdlsWLNmDZKTkxEfH4+bbroJra2tQYp4bE6dOoW7774bOTk5iImJwaRJk/DYY4/B4XBc9PtC+T189tlnMWHCBCiVShQVFaGmpuai57/zzjvIzc2FUqlEQUEBNm7cGKRIx27Dhg2YP38+VCoV0tLScMMNN6CxsfGi3/Pyyy8Pe6+USmWQIh6b//u//xsWa25u7kW/J5zeP2DkzxSRSIQ1a9aMeH6ov3/bt2/Hddddh4yMDIhEIrz//vs+xxljePTRR5Geno6YmBiUlJTg6NGjl3zesf4djxUlL0M4HA7cfPPNuO+++0Y87na7ce2118LhcODLL7/EK6+8gpdffhmPPvroRZ/39ttvR319PTZv3oyPP/4Y27dvx7333huIH2FMFi1ahJaWFp+v733ve8jJycG8efMu+r333HOPz/c98cQTQYp67H7xi1/4xPrAAw9c9PyHHnoIH330Ed555x1s27YNzc3NuPHGG4MU7dg0NDTA4/HghRdeQH19PZ566ik8//zz+N///d9Lfm8ovodvvfUW1q1bh8ceewx79uxBYWEhSktL0dbWNuL5X375JW677Tbcfffd2Lt3L2644QbccMMNOHjwYJAjH51t27ZhzZo1qKqqwubNm+F0OrFq1SpYrdaLfp9arfZ5r06fPh2kiMduxowZPrF+8cUXFzw33N4/ANi1a5fPz7d582YAwM0333zB7wnl989qtaKwsBDPPvvsiMefeOIJ/OUvf8Hzzz+P6upqxMXFobS0FDab7YLPOda/48vCyDAvvfQS02g0wx7fuHEjE4vFzGg08o8999xzTK1WM7vdPuJzHTp0iAFgu3bt4h8zGAxMJBKxc+fO+T32K+FwOFhqair7xS9+cdHzli5dyh588MHgBHWFxo8fz5566qlRn9/T08NkMhl75513+McOHz7MALDKysoAROh/TzzxBMvJybnoOaH6Hi5YsICtWbOG/7fb7WYZGRlsw4YNI57/jW98g1177bU+jxUVFbHvf//7AY3TX9ra2hgAtm3btguec6HPo1D02GOPscLCwlGfH+7vH2OMPfjgg2zSpEnM4/GMeDyc3j8A7L333uP/7fF4mE6nY7///e/5x3p6ephCoWBvvPHGBZ9nrH/Hl4NGXsagsrISBQUF0Gq1/GOlpaUwm82or6+/4PckJCT4jGSUlJRALBajuro64DGPxYcffojOzk7cddddlzz3tddeQ0pKCvLz87F+/Xr09fUFIcLL89vf/hbJycmYPXs2fv/73190mq+2thZOpxMlJSX8Y7m5ucjOzkZlZWUwwr1iJpMJSUlJlzwv1N5Dh8OB2tpan//2YrEYJSUlF/xvX1lZ6XM+wP1NhtN7BeCS71dvby/Gjx+PrKwsXH/99Rf8vAkFR48eRUZGBiZOnIjbb78dTU1NFzw33N8/h8OBV199Fd/97ncvuhFwOL1/Q508eRJGo9HnPdJoNCgqKrrge3Q5f8eXI+I2Zgwko9Hok7gA4P9tNBov+D1paWk+j0mlUiQlJV3we4Tyj3/8A6WlpZfc2PKb3/wmxo8fj4yMDOzfvx8//elP0djYiHfffTdIkY7e//zP/2DOnDlISkrCl19+ifXr16OlpQV//OMfRzzfaDRCLpcPq3nSarUh936N5NixY3j66afx5JNPXvS8UHwPOzo64Ha7R/wba2hoGPF7LvQ3GQ7vlcfjwdq1a3HVVVchPz//gudNmzYN//znPzFz5kyYTCY8+eSTWLRoEerr6wO+Ce1YFRUV4eWXX8a0adPQ0tKCxx9/HFdffTUOHjwIlUo17Pxwfv8A4P3330dPTw++853vXPCccHr/zud9H8byHl3O3/HliPjk5ZFHHsHvfve7i55z+PDhSxaVhZPL+ZnPnj2LTZs24e23377k8w+t1ykoKEB6ejpWrlyJ48ePY9KkSZcf+CiN5edbt24d/9jMmTMhl8vx/e9/Hxs2bAjp9t2X8x6eO3cOZWVluPnmm3HPPfdc9HuFfg8JsGbNGhw8ePCiNSEAUFxcjOLiYv7fixYtQl5eHl544QX88pe/DHSYY6LX6/n/P3PmTBQVFWH8+PF4++23cffddwsYWWD84x//gF6vR0ZGxgXPCaf3L5xEfPLy8MMPXzQrBoCJEyeO6rl0Ot2wimnvKhSdTnfB7zm/SMnlcqGrq+uC33OlLudnfumll5CcnIyvfvWrY369oqIiANxdfzAufFfynhYVFcHlcuHUqVOYNm3asOM6nQ4OhwM9PT0+oy+tra0Be79GMtafsbm5GcuXL8eiRYvw4osvjvn1gv0ejiQlJQUSiWTYyq6L/bfX6XRjOj9U3H///Xzx/ljvvmUyGWbPno1jx44FKDr/SUhIwNSpUy8Ya7i+fwBw+vRpbNmyZcyjleH0/nnfh9bWVqSnp/OPt7a2YtasWSN+z+X8HV8Wv1XPRJBLFey2trbyj73wwgtMrVYzm8024nN5C3Z3797NP7Zp06aQKtj1eDwsJyeHPfzww5f1/V988QUDwPbt2+fnyPzv1VdfZWKxmHV1dY143Fuw+5///Id/rKGhIaQLds+ePcumTJnCbr31VuZyuS7rOULlPVywYAG7//77+X+73W6WmZl50YLdr3zlKz6PFRcXh2zBp8fjYWvWrGEZGRnsyJEjl/UcLpeLTZs2jT300EN+js7/LBYLS0xMZH/+859HPB5u799Qjz32GNPpdMzpdI7p+0L5/cMFCnaffPJJ/jGTyTSqgt2x/B1fVqx+e6YIcPr0abZ37172+OOPs/j4eLZ37162d+9eZrFYGGPcL11+fj5btWoVq6urY+Xl5Sw1NZWtX7+ef47q6mo2bdo0dvbsWf6xsrIyNnv2bFZdXc2++OILNmXKFHbbbbcF/ee7kC1btjAA7PDhw8OOnT17lk2bNo1VV1czxhg7duwY+8UvfsF2797NTp48yT744AM2ceJEtmTJkmCHfUlffvkle+qpp1hdXR07fvw4e/XVV1lqaiq74447+HPO//kYY+wHP/gBy87OZp999hnbvXs3Ky4uZsXFxUL8CJd09uxZNnnyZLZy5Up29uxZ1tLSwn8NPSdc3sM333yTKRQK9vLLL7NDhw6xe++9lyUkJPAr/L797W+zRx55hD9/586dTCqVsieffJIdPnyYPfbYY0wmk7EDBw4I9SNc1H333cc0Gg3bunWrz3vV19fHn3P+z/j444+zTZs2sePHj7Pa2lp26623MqVSyerr64X4ES7q4YcfZlu3bmUnT55kO3fuZCUlJSwlJYW1tbUxxsL//fNyu90sOzub/fSnPx12LNzeP4vFwl/rALA//vGPbO/evez06dOMMcZ++9vfsoSEBPbBBx+w/fv3s+uvv57l5OSw/v5+/jlWrFjBnn76af7fl/o79gdKXoa48847GYBhX59//jl/zqlTp5her2cxMTEsJSWFPfzwwz6Z9+eff84AsJMnT/KPdXZ2sttuu43Fx8cztVrN7rrrLj4hCgW33XYbW7Ro0YjHTp486fPfoKmpiS1ZsoQlJSUxhULBJk+ezH784x8zk8kUxIhHp7a2lhUVFTGNRsOUSiXLy8tjv/nNb3xGyc7/+RhjrL+/n/3whz9kiYmJLDY2ln3ta1/zSQZCyUsvvTTi7+zQQdVwew+ffvpplp2dzeRyOVuwYAGrqqrijy1dupTdeeedPue//fbbbOrUqUwul7MZM2awTz75JMgRj96F3quXXnqJP+f8n3Ht2rX8fw+tVstWr17N9uzZE/zgR+GWW25h6enpTC6Xs8zMTHbLLbewY8eO8cfD/f3z2rRpEwPAGhsbhx0Lt/fPe806/8v7M3g8Hvbzn/+cabVaplAo2MqVK4f93OPHj2ePPfaYz2MX+zv2BxFjjPlvEooQQgghJLCozwshhBBCwgolL4QQQggJK5S8EEIIISSsUPJCCCGEkLBCyQshhBBCwgolL4QQQggJK5S8EEIIISSsUPJCCCGEkLBCyQshhBBCwgolL4QQQggJK1KhA/A3j8eD5uZmqFQqiEQiocMhhBBCyCgwxmCxWJCRkQGx+OJjKxGXvDQ3NyMrK0voMAghhBByGc6cOYNx48Zd9JyIS15UKhUA7odXq9UCR0MIIYSQ0TCbzcjKyuKv4xcTccmLd6pIrVZT8kIIIYSEmdGUfFDBLiGEEELCCiUvhBBCCAkrlLwQQgghJKwImrz89re/hUgkwtq1a/nHbDYb1qxZg+TkZMTHx+Omm25Ca2urcEESQgghhOdsa4OtsVHQGARLXnbt2oUXXngBM2fO9Hn8oYcewkcffYR33nkH27ZtQ3NzM2688UaBoiSEEEKIq7MT3W+8gdPfvgPHli6D8Ze/FDQeQVYb9fb24vbbb8ff/vY3/OpXv+IfN5lM+Mc//oHXX38dK1asAAC89NJLyMvLQ1VVFRYuXChEuIQQQkjUcXV3w7J5Myzl5bBWVQMez+BBtwcehwNiuVyQ2ARJXtasWYNrr70WJSUlPslLbW0tnE4nSkpK+Mdyc3ORnZ2NysrKEZMXu90Ou93O/9tsNgc2eEIIISRCuU0mWLZUwFxeDmtlJeBy8ceU+flQ6/VQl5VClpkpYJQCJC9vvvkm9uzZg127dg07ZjQaIZfLkZCQ4PO4VquF0Wgc8fk2bNiAxx9/PBChEkIIIRHP3duL3ooKmA3l6N25E3A6+WOKvDwuYdGXQR5C3euDmrycOXMGDz74IDZv3gylUumX51y/fj3WrVvH/9vboY8QQgghI/NYrbBs3QqzwQDr9h1gDgd/TDFlCtSr9VCVlUGRkyNglBcW1OSltrYWbW1tmDNnDv+Y2+3G9u3b8cwzz2DTpk1wOBzo6enxGX1pbW2FTqcb8TkVCgUUCkWgQyeEEELCmqe/H73btsNsMKB32zYwm40/Js/J4UZYVuuhmDxZwChHJ6jJy8qVK3HgwAGfx+666y7k5ubipz/9KbKysiCTyVBRUYGbbroJANDY2IimpiYUFxcHM1RCCCEk7Hnsdlh37IB5owGWrVvB+vr4Y7Ls7MGEZerUUbXlDxVBTV5UKhXy8/N9HouLi0NycjL/+N13341169YhKSkJarUaDzzwAIqLi2mlESGEEDIKzOFA786d3AhLxWfwWK38MVlmJtT6Mqj0eiinTw+rhGWokNuY8amnnoJYLMZNN90Eu92O0tJS/PWvfxU6LEIIISRkMacT1qoqboSlogKeIStvpTod1GVlUK/WQ1lQELYJy1AixhgTOgh/MpvN0Gg0MJlMtKs0IYSQiMVcLvTV1MBsKIdl82a4e3r4Y9LUVKjKyqDW6xEzqxAicejvBjSW63fIjbwQQgghZGTM7UZfbS3MBgMsn26Gu7OTPyZJToa6dBWXsMyZA5FEImCkgUXJCyGEEBLCmMeD/ro6bkpo0ya42tv5Y5KEBKhWrYJaX4bY+fMhkkbHZT06fkpCCCEkjDDGYNu/H+aNBpg3bYJrSKNWsVoNVUkJ1Ho94hYWQSSTCRipMCh5IYQQQkIAYwy2+kMwGzbCYiiHs7mZPyaOi4OqZCVUej3iFy2CSKA9hUIFJS+EEEKIQBhjsDc2ciMs5eVwNjXxx0SxsVAtXw71aj3iFi+GmBqy8ih5IYQQQoLMfvQozAYDzIZyOE6e5B8XKZWIX7YMar0e8UuXQOynrXQiDSUvhBBCSBDYT57kVgkZDLAfPcY/LpLLEb90yUDCshTiuDgBowwPlLwQQgghAeJoaoLZUA6zwQB7Q8PgAZkM8YsXQ60vQ/yKFZDExwsXZBii5IUQQgjxI+e5czCXl8O80QBbff3gAakUccXFUOv1UJWshIQaqV42Sl4IIYSQK+Q0GrmExWCAbd/+wQMSCeKKiqDSl0FVUgJpYqJwQUYQSl4IIYSQy+Bsa4Nl06cwGwzo37Nn8IBIhNgFC7gNEFetgjQpSbggIxQlL4QQQsgouTo7Yfn0U5gN5ejbtQsYsj1gzNy5UOv1UJeugjQ1VcAoIx8lL4QQQshFuLq7Ydm8GZbyclirqgGPhz8WU1gI9Wo9VGVlkGm1AkYZXSh5IYQQQs7jNpth2VIBs8EAa2Ul4HLxx5T5+dwIS1kpZJmZAkYZvSh5IYQQQgC4e3vR+9lnMG80oHfnTsDp5I8p8vL4hEWenS1glASg5IUQQkgU81itsGzdyo2wbN8B5nDwxxRTpvBTQoqcHAGjJOej5IUQQkhU8fT3o3fbdpgNBvRu2wZms/HH5Dk53AjLaj0UkycLGCW5GEpeCCGERDyP3Q7rjh0wbzTAsnUrWF8ff0yWnT2YsEydCpFIJGCkZDQoeSGEEBKRmMOB3p07uRGWis/gsVr5Y7LMTK4Pi14P5fTplLCEGUpeCCGERAzmdMJaVcWNsFRUwGM288ekOh3UZWVQr9ZDWVBACUsYo+SFEEJIWGMuF/pqamA2lMOyeTPcPT38MWlqKlRlZVDr9YiZVQiRWCxcoMRvKHkhhBASdpjbjb7aWpgNBlg+3Qx3Zyd/TJKcDHXpKi5hmTMHIolEwEhJIFDyQgghJCwwjwf9dXXclNCmTXC1t/PHJAkJUK1aBbW+DLHz50MkpctbJKN3lxBCSMhijMG2fz/MGw0wb9oEl9HIHxOr1VBdUwJ1mR5xC4sgkskEjDQ6MMZw2nwaZocZM1NnChYHJS+EEEJCCmMMtvpDMBs2wmIoh7O5mT8mjo+HauVKqPRliF+0CCK5XMBIo0N7XzuqjdWoaq5CtbEaRqsRBSkFeP3a1wWLiZIXQgghgmOMwd7YyI2wlJfD2dTEHxPFxkK1fDnUq/WIW7wYYoVCwEgjn8VhwW7jbj5hOW467nNcJpYhVhYLt8cNiViYeqKgJi/PPfccnnvuOZw6dQoAMGPGDDz66KPQ6/UAAJvNhocffhhvvvkm7HY7SktL8de//hVa2qmTEEIikv3oUZgNBpgN5XCcPMk/LlIqEb9sGdR6PeKXLoFYqRQwysjmcDuwr30fqlqqUNVShfqOeriZmz8uggh5yXkoSi/CwvSFmJ02GzHSGAEjDnLyMm7cOPz2t7/FlClTwBjDK6+8guuvvx579+7FjBkz8NBDD+GTTz7BO++8A41Gg/vvvx833ngjdu7cGcwwCSGEBJD9xEmYyw2wGAywHz3GPy6SyxG/dMlAwrIU4rg4AaOMXB7mQUNXA6paqlDdUo09rXtgc9t8zhmvHo+F6QtRlF6EBboF0Cg0AkU7MhFjjAkZQFJSEn7/+9/j61//OlJTU/H666/j61//OgCgoaEBeXl5qKysxMKFC0f1fGazGRqNBiaTCWq1OpChE0IIGSVHUxPMhnKYDQbYGxoGD8hkiF+8GOrVesQvXw5JfLxwQUYoxhiaLE2obqlGVUsVaow1MNlNPuckK5OxMGMhinTc6Ep6fHrQ4xzL9Vuwmhe324133nkHVqsVxcXFqK2thdPpRElJCX9Obm4usrOzx5S8EEIICQ2Os+dg2VQO80YDbPX1gwekUsQtKoZavxqqlSsgoRtNv+vo7+CTleqWarRYW3yOx8niMF87n58KmpQwKaw6Dgc9eTlw4ACKi4ths9kQHx+P9957D9OnT0ddXR3kcjkSEhJ8ztdqtTAOWRp3PrvdDrvdzv/bPKQVNCGEkOByGo0wl3MjLLZ9+wcPSCSIKyriRlhWroQ0MVG4ICNQr6MXu1t38wnLsZ5jPselYilmpc7ip4LyU/IhFYfvmp2gRz5t2jTU1dXBZDLhP//5D+68805s27btsp9vw4YNePzxx/0YISGEkLFwtrXBsulTmA0G9O/ZM3hAJELsggVQ6/VQrboG0qQk4YKMMN4iW2+ycrDj4LAi29ykXD5ZmZ02G7GyWAEj9i/Ba15KSkowadIk3HLLLVi5ciW6u7t9Rl/Gjx+PtWvX4qGHHhrx+0caecnKyqKaF0IICSBXZycsn34K80YD+nbvBryXEpEIMXPnQF2mh7p0FaSpqcIGGiE8zIPGrkZ+Gqi2tXZYkW22KpufBlqgW4AEZYIwwV6msKh58fJ4PLDb7Zg7dy5kMhkqKipw0003AQAaGxvR1NSE4uLiC36/QqGAgtb8E0JIwLm6u2HZvBlmgwF91TWAx8MfiykshHq1HqqyMsiovcUVY4zhjOUMn6zUGGvQY+/xOSdJmYSi9CIUpxejKL0IGfEZwgQrgKAmL+vXr4der0d2djYsFgtef/11bN26FZs2bYJGo8Hdd9+NdevWISkpCWq1Gg888ACKi4upWJcQQgTiNplg2VIBc3k5rJWVgMvFH1Pm50Ot10NdVgpZZqaAUUaGjv4O1LTU8AlLs7XZ53isNBbzdVyRbVF6EaYkTAmrIlt/Cmry0tbWhjvuuAMtLS3QaDSYOXMmNm3ahGuuuQYA8NRTT0EsFuOmm27yaVJHCCEkeNy9veitqIDZUI7enTsBp5M/psjL4xIWfRnkWVkCRhn+rE4rdht3c8mKsRpHu4/6HJeKpShMLeRHV2akzIBMTPs3ASFQ8+Jv1OeFEELGzmO1wvL5VpjLDbBu3wHmcPDHFFOm8FNCipwcAaMMb063kyuyHWi7f7DjIFzM5XNOblIu12slYyHmpM2JqCLbSwmrmhdCCCHC8PT3o3fbdpgNBvRu2wZmGywAlU+cyI+wKCZPFjDK8OVhHhzpPoLqlmpUtlRiT+se9Lv6fc4ZFz+Oaw430Mk2SUkrskaDkhdCCIkiHrsd1h07YN5ogGXrVrC+Pv6YbHz2QMKih2Lq1Kitp7gSPkW2LTXotnf7HE9SJqFIV8TXrYxTjRMo0vBGyQshhEQ4j8MB686d3AhLxWfwWK38MVlmJj8lpJw+nRKWMers70SNsYbvt3Ku95zP8RhpDOZp5/FLmKckToFYJBYo2shByQshhEQg5nTCWlXFjbBs2QKPxcIfk+p0UJeVQb1aD2VBASUsY9Dn7MPu1t386MqR7iM+x6UiKWamzuSbwxWkFEAmoSJbf6PkhRBCIgRzudBXUwOzwQDLp5vhNg1uvidNTYWqrAxqvR4xswohEtPd/2g4PU4caD/AJyv72/cPK7KdljiNnwaap50XVUW2QqHkhRBCwhhzu9G3uxZmw0YuYenq4o9JkpOhLl3FJSxz51LCMgoe5sHR7qN8srK7dfewItvM+EwsTF+IhekLMV83H8kxyQJFG70oeSGEkDDDPB70790Ls6Ec5k3lcLd38MckCQlQrVoF9Wo9YufNg0hKH/OXctZylq9ZqTHWoMvW5XM8UZGIBekL+KmgLBX1txEa/VYTQkgYYIzBtm/fQMKyCS6jkT8mVquhuqYEav1qxBUtgEhGNRYX02XrQo2xBlXN3OjK2d6zPsdjpDGYq53Lj65QkW3ooeSFEEJCFGMMtoP1MJcbYDGUw9k82C5eHB8P1cqVUK/WI664GCK5XMBIQ1ufsw+1rbX86Epjd6PPcalIioLUAn5F0MyUmVRkG+IoeSGEkBDCGIO9oYEbYSkvh7OpiT8mjo1F/IoVUOvLELd4McS0Ke2InB4nDnYcRFVLFaqaq7C/Yz9cHt8i2ymJU/iRlbnauYiTxQkULbkclLwQQkgIsB05Akt5OcwbDXCcOsU/LlIqEb98GdRlesQvXQKxUilYjKGKMYajPUf5kZXdxt3oc/X5nJMRl8F1stUVYUH6AqTEpAgULfEHSl4IIUQg9hMnYTZshNlggOPYcf5xkVyO+KVLoNbrEb9sGcSxtPT2fM29zdzIysCqoPOLbBMUCVigW8BvajhONY762UQQSl4IISSIHE1NMG80wFxeDntDw+ABmQzxixdDvVqP+OXLIYmPFy7IENRt6/bpZHvGcsbneIw0BnPS5vArgqYlTaMi2whGyQshhASY4+w5WMoNMBvKYauvHzwglSJuUTHU+tVQrVwBySV20o0mfc4+7G3byycrDV0NYGD8cYlIgoKUAr45XGFqIeQSKlqOFpS8EEJIADhbWmAu3wRzuQG2ffsHD0gkiCsqgkpfBlVJCaSJicIFGUJcHhdfZFvdUo269rphRbaTEyb7FNnGy2l0KlpR8kIIIX7ibGuDpXwTzOXl6N+zZ/CASITYBQug1pdBtWoVpElJwgUZIhhjON5znE9WdrXugtVp9TknPS6dH1lZmL6QimwJj5IXQgi5Aq7OTlg+/RTmjQb07d4NsMGpjZi5c6HW66EuXQVpaqqAUYaGlt4Wvsi2xliDjv4On+MahQYLdAv40ZUsVRYV2ZIRUfJCCCFj5OruhmXzZpgNBvRV1wAeD38sprAQ6tV6qMrKINNqBYxSeCa7abCTrbEap82nfY4rJUrM0c7hR1Zyk3KpyJaMCiUvhBAyCm6TCZYtFTAbDLBWVgJuN39MmZ/PjbCUlUKWmSlglMLqd/Vjb+teVBm55nAjFdnOSJnBj6xQkS25XJS8EELIBbh7e9FbUQHzRgN6v/wScDr5Y4q8PD5hkWdnCxilcFweF+o76/kVQXVtdXB6nD7nTNJM4pvDzdPNg0quEihaEkkoeSGEkCE8Vissn2/lRlh27ABzOPhjiilToNKXQa3XQ5GTI2CUwmCM4YTpBF+3stu4G73OXp9ztLFavtdKUXoR0mLTBIqWBISjD2g7DDj7gJyrBQuDkhdCSNTz9Pejd9s2boRl2zYwu50/Js/J4UZY9GVQTJkiYJTCMFqN/Iqg6pZqtPe3+xxXy9V8kW1RehHGq8dTkW2ksHYAxv1Ay37AeID76jwKMA+gmwn8YIdgoVHyQgiJSh67Hb3bt8NiKIdl61awvsG9cGTZ2VzCsloPxdSpUXUxNtlN2GXcxScsp8ynfI4rJArMTpvN163kJuVCIpYIEyzxD48H6D7JJSreJMV4ALC0jHx+bAqgzuRW1gn0t0HJCyEkangcDlh37oTZYEBvxWfwWAf7isgyM7k+LHo9lNOnR03CYnPZsLdtL5+sHOo85FNkKxaJkZ+cz08DzUqbBYWEdrMOW04b0HbIN0lpPQg4ekc4WQQkTQTSZwK6Am60RVcAxGsFS1q8KHkhhEQ05nTCWlUF80YDLFu2wGOx8MekOh3UZWVQr9ZDWVAQFQmLy+PCoc5D/DTQ3ra9cHgcPudM1Ezkly/P082DWk7bFoSlvq7hoyntjQBzDz9XogC00wcTFN1M7t+K0CywpuSFEBJxmMuFvpoamA0GWD7dDLfJxB+TpqZCVVYGtb4MMbNmQSSO7L4ijDGcNJ30KbK1OC0+56TFpvHTQAt0C6CNi+7+NGGHMaD7lG+SYjwAmM+OfH5M0vDRlOQpgCR8UoLwiZQQQi6Cud3o210Ls2Ejl7B0dfHHJElJUJWuglqvR+zcuRBJIrtGo9XaimpjNdccrqUabf1tPsdVMhUWpC/gp4Jy1DlRMeoUEVx2oL1hMEFp2c9N+9jNI5+fmOObpOgKAHWG4NM+VyqoycuGDRvw7rvvoqGhATExMVi0aBF+97vfYdq0afw5NpsNDz/8MN58803Y7XaUlpbir3/9K7RR3qmSEDIc83jQv3cvzIZymDeVw90+2G5ekpAA1TXXQL1aj9j58yGSRu69msluwm7jbq5uxViNk6aTPsflYjlmaweLbPOS8qjINhz0dwPGgwOJysD0T3sDcN6GlQAAiRxIy/NNVLQzAKUm+HEHQVD/mrdt24Y1a9Zg/vz5cLlc+N///V+sWrUKhw4dQlxcHADgoYcewieffIJ33nkHGo0G999/P2688Ubs3LkzmKESQkIUYwy2ffsGEpZNcBmN/DGxWg1VSQnUej3iFhZBJJMJGGng2N127G3byzWHa67Coa5D8LDBLQrEIjGmJ03n6lYyFmJW6iwopUoBIyYXxRhgOuO7JNl4ADA1jXy+MmH4aErKVEAaPd2KRYwN2UUsyNrb25GWloZt27ZhyZIlMJlMSE1Nxeuvv46vf/3rAICGhgbk5eWhsrISCxcuvORzms1maDQamEwmqNVUZEZIJGCMwVZ/iJsSMpTD2dzMHxPHxUFVshIqvR7xixZBJI+8D3C3x43DXYf5upW6tjrY3XafcyaoJ/AjK/N086BRROYdd9hzOYCOxvPqU/YDNtPI5ydk+yYpupmAZlzYT/uMZCzXb0HHUU0DRXRJA9vD19bWwul0oqSkhD8nNzcX2dnZF0xe7HY77EMaSpnNF5j3I4SEFcYY7I2NMG80wFxeDmfT4F2oKDYWquXLoV6tR9zixRArImvpLmMMp8yn+OXLNcYaWBznFdnGpPE1K0XpRdDF6QSKllyQzTRk2mcgSWlvANyO4eeKpUBq3pAkpQDQ5QMxicGPOwwIlrx4PB6sXbsWV111FfLz8wEARqMRcrkcCQkJPudqtVoYhwwND7VhwwY8/vjjgQ6XEBIk9qNHYTYYYDaUw3FysHZDpFQiftkyqPV6xC+5GuKYGAGj9L+2vjZ+j6Cqliq09Q0vsp2nm8ePruRoqMg2ZDAGmM/5JinGA9wKoJEo1OclKTOB1GmANLKS8EASLHlZs2YNDh48iC+++OKKnmf9+vVYt24d/2+z2YysrKwrDY8QEkT2Eye5KaHyctiPHuMfF8nliF+6BKqyMqiWLYN4oDYuElgcFp9OtidMJ3yOy8QyvpNtUXoRpidPh1QcuUXHYcPtAjqO+CYpxgNAf9fI56vH+SYq6TOBhPEROe0TTIL8Jdx///34+OOPsX37dowbN45/XKfTweFwoKenx2f0pbW1FTrdyEOiCoUCiggbMiYkGjiamriiW4MB9oaGwQMyGeIXL4ZaX4b4FSsgiY8XLkg/srvt2Ne2j09WDnYe9CmyFUGE6cnT+Wmg2WmzESONrNGlsGO3AK31volK6yHgvHojAIBIwo2eDB1N0RUAsUnBjzsKBDV5YYzhgQcewHvvvYetW7ci57xdWefOnQuZTIaKigrcdNNNAIDGxkY0NTWhuLg4mKESQgLAcfYcLJvKYd5ogK2+fvCAVIq44mKo9XqoSlZCEgHF9m6PGw1dDXyysqdtz4hFtt5OtvN186nIViiMARbjeaMp+4GuEyOfL48HtPlDGr0VcPUqMlrRFSxBTV7WrFmD119/HR988AFUKhVfx6LRaBATEwONRoO7774b69atQ1JSEtRqNR544AEUFxePaqURIST0OI1GmMu5ERbbvv2DB8RixC0sgkqvh6qkBNLE8C5MZIzhtPk0X7dSY6yB2eG7gCAlJoVPVhamL6QiWyF43EDnMd9EpWU/0Ncx8vmqjPPqUwq4xm8R3pk51AV1qfSFisteeuklfOc73wEw2KTujTfe8GlSd6Fpo/PRUmlChOdsa4Nl06cwGwzo37Nn8IBIhNj586FerYfqmmsgTU4WLkg/aO9r50dWqo3VMFp9FxbEyeIwXzefT1YmaiZSkW0wOazcNM/Q2pTWesDVP/xckZjrlTI0SdEWAPGpwY87So3l+i1on5dAoOSFEGG4Ojth+fRTmA3l6Nu1ixuKHxAzdy43JbTqGsjS0gSM8spYHBbsNu7mW+8fNx33OS4TyzArbRaKdFxzuBnJM6jINlh623yTlJb93AgLRrjEyWK5aZ+h9SlpeYA8Nuhhk0Fh0+eFEBLeXN3dsGzeDEt5OaxV1YBnsAA1prCQG2EpLYVslCOnocbhdmBf+z5++XJ9Rz3cQ3bkFUGE3KRcLMxYiIW6hZitpSLbgPN4uFoUn92S9wO9rSOfH68dviw5aSJA2yOENUpeCCFj4jabYdm8BebyclgrKwHX4D4ryhkzoF6th7qsDLLMTAGjvDwe5vEtsm3dA5vb5nNOtiqbX768QLcACcoEYYKNBs5+oO3Qed1oDwJO6wgni4Dkyb5LkrUFgIr2xYtElLwQQi7J3duL3s8+g3mjAb07dwJOJ39MkZcHdVkZ1PoyyLOzBYxy7BhjOGM5w4+s1BhrYLL7tmlPVibzRbZF6UXIiM8QKNoIZ+30XeljPMD1UxmynJwnVXKbDvJLkmcC2umAPHL6AJGLo+SFEDIij9UKy9atMBsMsG7fAeYYbGmumDIFKn0Z1GV6KCbmXORZQk9HfwdXYDuwKqjF2uJzPE4Wh3naeXyyMjlhMhXZ+pPHA/ScGqxL8Y6oWJpHPj82eTBJSS/k/n/SJEBCl69oRu8+IYTn6e9H77btMBsM6N22Dcw2OGUiz8mBWq+HWl8GxZQpAkY5Nr2OXtS21vKjK8d6jvkcl4qlmJU6ix9dmZEyAzJxZO5GHXQuO9B2+Lz6lIPAefs08ZImDtmEcOB/VTrqRkuGoeSFkCjnsdth3bED5o0GWLZuBevr44/JsrO5hGW1HoqpU8NiBMJbZOsdWTnYcdCnyBYA8pLy+GRldtpsxMpolckV6+s6rzblALd7ssc1/FyJgpvmGZqkaGcAClXw4yZhiZIXQqIQczjQu3MnN8JS8Rk81sECSFlmJtT6Mqj0eiinTw/5hMXDPGjsauSTlT1te9B/Xh+PLFUWn6ws0C1AojK8G+IJijGg5/TwRMV0ZuTzYxKHj6akTAEkNLpFLh8lL4RECeZ0wlpVBbOhHJYtW+AxD3Z/lep0XNHtaj2UBQUhnbAwxnDWchZVxipUNXNFtj32Hp9zkpRJPkW2mfHht/IpJLgcQHvD8ETlvKJmXuIE3yRFVwCoM2nah/gdJS+ERDDmcqGvpoZLWDZvhrunhz8mTU2FamCVUMysWRCFcLvzjv4O1LTU8M3hmq2+xZ2x0ljM083jm8NNSZgS0glYSOrvAVoP+vZOaWsAPM7h54plXFM3b5KSPpOb9lHS3kwkOCh5ISTCMLcbfbW1MBsMsHy6Ge7OTv6YJCkJqtJVUOv1iJ07FyJJaDbqsjqtPkW2R7uP+hyXiqWYmTKTaw6XvhD5KflUZDtajAGms75JinE/0NM08vlKzQjTPlMBqTy4cRMyBCUvhEQA5vGgv66OK7rdtAmu9nb+mCQhAaprroF6tR6x8+dDJA29P3un24n9Hfv55nAH2g/AxXwLPaclTuOngeZq51KR7Wi4nVyvFH5Z8sCqH1vPyOdrsgdHUrzTPposmvYhISf0PsUIIaPCGINt/36YNxpg3rQJLuPgpoBitRqqkhKo9XrELSyCSBZaoxIe5sHR7qP8yEpta+2wIttx8eO4upUMrsg2SZkkULRhwmbmNh00DklS2g4Dbsfwc8VSIDXXtzZFl88V1xISBih5ISSMMMZgqz8Es2EjLIZyOJsHaz/EcXFQlayESq9H/KJFEMlDa1j/jOUMvyKopqUG3fZun+NJyiQs0C3gR1fGqcYJFGmIYwywtAxp8Dbwv90nRz5foT5vb58CLnGRKoIbNyF+RMkLISGOMQZ7YyM3wlJeDmfTYG2CKDYWquXLoV6tR9zixRArQueC1GXrQk1LDT+6cq73nM/xGGkM5mrnYmE6V7cyJXEKxKLQLRoWhNvF7Yw8dDTFeADo6xz5fPW48xKVfCBhAhDCxdiEXA5KXggJUfajR2E2GGA2lMNxcvCuWqRUIn7ZMqj1esQvXQKxUilglIP6nH18kW11SzUauxt9jktFUsxMnckvYS5IKYCMen0MsvdymxC27BtMUtoOAS7b8HNFEiB1mm+ioi0A4pKDHzchAqDkhZAQYj9xEuZyAywGA+xHB9vYi+RyxC9dMpCwLIU4TvgN6JweJw60H+Cngva37x9WZDs1cSqfrMzVzkWcTPi4Q4KldSBBGZKodB4HwIafK48HtPm+iUpaHiCLCXrYhIQKSl4IEZijqQlmQznMBgPsDQ2DB2QyxC9eDPVqPeKXL4ckPl64IOFbZFvdUo3a1lr0ufp8zsmIy+CXLy/QLUByTJSPBHjcQNcJ39EU4wHA2jby+ar086Z9ZgKJOTTtQ0KC2eZES48NzSauuH75tDTBYqHkhRABOM+dg7m8HOaNBtjq6wcPSKWIW1QMdZkeqpKVkKjVwgUJ4FzvOVQ1c8lKtbEaXbYun+MJigQUpRfxoytZqiyBIg0Bjr6BTQiHJCqt9YCzb/i5IjGQPGV4IW28cBcDEt36HC4099jQYupHS48NLSbu/zebbGjp6UeLyYZe++DI6jStipIXQqKB02jkEhaDAbZ9+wcPSCSIK1oAlV4PVUkJpInCLVfttnWj2ljNTQU1V+Fs71mf4zHSGMzRzkFxejGK0oswNXFqdBbZWju4AtqWIUW0nUcB5hl+riyW6z47dDQlbTogpz41JDhsTjeMJm7ExGjiEpPmgYTE+7+m/hE6KY9AEyNDukaJqVphN9Gk5IWQAHK2tcGy6VOYDQb079kzeEAkQuyCBdwGiKtWQZokTA+TPmcf9rTt4UZXjNVo6GrwOS4RSVCQUoCFGQtRpCtCYWphdBXZejzcEuShK32MB7ilyiOJSz2vd8pMIHkSIA7NTsYk/DndHhhNNhjNg4lIS8/AiMnAKEqndYRePyOIV0iRrlEiPSEGGRol0jUxSE9QIkMTA51GiYwEJWLloZE2hEYUhEQQV2cnLJ9+CrOhHH27dnF9OQbEzJ0LtV4PdekqSFNTgx6b0+NEfUc9KlsqUd1SjX3t++Dy+BbZTkmcwu0RNFBkGy8XttYmaJw2oP2w72hK60HA0TvCySIuKRmapOhmAipt0MMmkcvtYWi32NHMT+X081M73umc9l770I+YC1LKxMgYSEbSNVxyohuSnKQnKKFWhs+NCSUvhPiBq7sbls2bYSkvh7WqmrtjHxBTWAj1aj1UZWWQaYN7cWOM4WjPUa5mpaUau4y7hhXZpsel871WFqQvQEpMSlBjFERf1/DRlPZGgLmHnytVctM8QxMV7QxAESVJHQkIj4eh0+rwSUiGTuO09PSj1WKH23PpzEQuEUOnUSJdo0RGwsAoyXkjJwmxsojarJSSF0Iuk9tkgmVLBczl5bBWVgKuwREMZX4+N8JSVgpZZmZQ42rubUZ1SzUqWypR01KDTptvQzONQsN3svUW2UbSh5oPxoDuU75JivEAYD478vkxSQM7JOcD6YVcspI8BZDQRyUZPcYYevqcviMmQwpfW0w2GE02ONwj1EidRyIWQafmEhPdQHKSPpCYZAyMoiTHySEWR+jf8AXQXyQhY+Du7UXvZ5/BvNGA3p07AedgkZsiL49LWPRlkGcFb9VNj62HL7KtbqlGk8V3d2ClRIm52rn8qqDcpNzILLJ12YH2huGJit088vmJOYMjKd6NCFXptAkhuaShS4aHTucYzf384zbnpRMTkQhIjVf41Jh4ExLviEmqSgFJlCUmo0HJCyGX4LFaYdm6FWaDAdbtO8Acg8VviilT+CkhRU5OUOLpd/VjT+sevjlcQ1cD2JDmZhKRBPkp+fzy5cLUQsglobXP0RXr7waMB4ckKfu5xOW8+h0AgETONXXTFQC6gdEU7QxAKewydBKaxrpk+GKS4+Q+NSbpA6Mm3tETrVoJmSQCbySCgJIXQkbg6e9H77btMBsM6N22Dcw22KJdnpPDjbCs1kMxeXLAY3F5XDjYcZBPVva174PT47uscXLCZH5Dw3naeZFTZMsYYDozmKR4i2lNTSOfr0zgkhPvlI+uAEiZCkTTCilyQYFYMpxxXkLiHT3RqpVQymiVWaBQ8kLIAI/dDuuOHTBvNMCydStY32Bhqyw7ezBhmTo1oDUijDEc7znOd7Ld3bobvU7fFS+6OB2frBTpipAaG/yVS37ndnJFs0N3SjbuB2ymkc9PGD9kpc9AoqIZR9M+USpalwxHq6D/19++fTt+//vfo7a2Fi0tLXjvvfdwww038McZY3jsscfwt7/9DT09Pbjqqqvw3HPPYcqUKcEOlUQB5nCgd+dOboSl4jN4rFb+mCwzk+vDotdDOX16QBOWlt4WLlkZqF3p6O/wOa6Wq/lEZWHGQmSrssO7yNZmGnnaxz3CxUUsA9JyfZMUbT4QkxD0sIkwAr1kOJ1foRN+S4ajVdCTF6vVisLCQnz3u9/FjTfeOOz4E088gb/85S945ZVXkJOTg5///OcoLS3FoUOHoAyR3XNJeGNOJ6xVVdwIS0UFPObBgk6pTgd1WRnUq/VQFhQELEEw2U2oMdbwU0Gnzad9jiskCsxJm8M1h0svQm5iLiTh2OiMMcDc7DuSYjzArQAaiUIzvGV+ai4gjbCaHcIL5JLh9IH/H8lLhqNV0JMXvV4PvV4/4jHGGP70pz/h//2//4frr78eAPCvf/0LWq0W77//Pm699dZghkoiCHO50FdTA7PBAMunm+E2DU5FSFNToSorg1qvR8ysQogCsAlev6sfe9v28lNBhzsP+xTZikVi5CcPKbJNK4RCovB7HAHldgEdR86b9jkA9HeNfL4ma/gmhAnZNO0TQS62ZLh5YLkwLRkmlyOkJu1OnjwJo9GIkpIS/jGNRoOioiJUVlaOmLzY7XbY7Xb+32bzBZZFkqjD3G707a6FudwAy6ZP4e4avIhKkpOhLl3FJSxz5/o9YXF5XKjvrOeXL+9t2zusyHaSZhK/fHmebh7U8jBa/WK3cJsODk1UWg8Bbvvwc0USbvTEm6R4+6jECrMlAvEffy4ZTlMpoNPQkmEyOiGVvBiNRgCA9rwupFqtlj92vg0bNuDxxx8PeGwkPDCPB/11ddyU0KZNcLW388ckCQlQrVoFtb4MsfPnQyT1368/YwwnTCdQ1VKFqpYq7DYOL7LVxmr5kZWi9CKkxYbBDsKMARbj8NGUrhMARhjGl6sAXb5vIW1qLiCjKd9wc/6SYe8KHVoyTEJBSCUvl2P9+vVYt24d/2+z2YysIDYII8JjjMG2fz/MGw0wb9oE15BEV6xWQ3VNCdRlesQtLIJI5r9CPKPVyNesVLdUo72/3ee4Sq5Cka6IH12ZoJ4Q2nPtHjfQeWx4omJtH/l8VYbvaIquAEiYAARg2o3419Alwy09vit0aMkwCQchlbzodDoAQGtrK9LT0/nHW1tbMWvWrBG/R6FQQKEIs9oAcsUYY7DVH4LZsBEWQzmczc38MXF8PFQrV0KlL0P8okUQyf1T7Gmym7DLuItPVk6ZT/kcV0gUmJ02G0XpRShOL0ZuUggX2Tqs3DTP0CSltR5w9Q8/VyTmeqWcvyw5Lgr2QApDwVoyzI2k0JJhIoyQ+q3LycmBTqdDRUUFn6yYzWZUV1fjvvvuEzY4IjjGGOyNjdwIS3k5nE2DjcrEsbGIX7ECan0Z4hYvhtgPCa3NZcPetr386MrhrsPwsMH5e7FIjBnJM/hpoFlps0KzyLa3zTdJadnPjbCMNO0jix3Y12dIkpI2HZDFBD1sMhwtGSaEE/Tkpbe3F8eOHeP/ffLkSdTV1SEpKQnZ2dlYu3YtfvWrX2HKlCn8UumMjAyfXjAkutiPHoXZYIDZUA7HyZP84yKlEvHLlkGt1yN+6RKIr3ApvdvjxqHOQ/zIyt62vXB4fO9QJ2om8tNA83XzQ6vI1uPhalF8dkveD/S2jnx+vPa80ZSZQFIOEKqjRRGOdhkmZPSCnrzs3r0by5cv5//trVe588478fLLL+MnP/kJrFYr7r33XvT09GDx4sUoLy+nHi9Rxn7iJDclVF4O+9HBZFcklyN+6RIuYVm2DOLY2Mt+DcYYTppPoqqZS1Z2GXfB4rT4nJMWm8bvvrxAtwDaOO0Fni3InP1A26HzNiE8CDitI5wsApIn+9amaAsAVYj8LFHgUkuGW0z9aDXZx7xkOP28Xia0ZJhECxFjoxlgDB9msxkajQYmkwlqdQjdFZNLcjQ18VNC9oaGwQMyGeIXL4Z6tR7xy5dDEn/5+/a0Wlv5LrZVzVVo62/zOa6SqbAgfQE/upKjzhH+7tTaOXw0peMIwEa40EmV3KaDQ0dTtNMBeVzw444iF1oy3MKv0KElw4Rcyliu3yFV80Kij+PsOVg2lcO80QBbff3gAakUcYuKodavhmrlCkguMxE1O8xckW0z13r/pOmkz3G5WI7Z2tn86EpeUp5wRbYeD9Bzync0pWU/YGke+fzYZC45SZ85mKwkTQIk9GftTyMtGW7psaHFPPYlwynx8oHpHFoyTMiVoE85EnROoxHm8nKYDQbY9u0fPCCRIK6oCCp9GVQlJZAmJo75ue1uO+ra6vi6lfrO+mFFttOTpvNt92elzoJSKsCUpMsOtB32HU0xHgQclpHPT5roO5qiKwBUOupGe4VoyTAh4YmSFxIUzrY2WDZ9CrPBgP49ewYPiESIXbCA2wBx1SpIk8bWddXtceNw12G+OVxdWx3s53V5zdHkcBsapi/EPN08aBQaf/xIo9fXBbQeHBxJMR4AOhoBzwh36xIFN80zNEnRzgAUquDGHAG8S4ZbTIPFr7RkmJDIQH9tJGBcnZ2wfPopzBsN6Nu9G0PXb8bMnQu1Xg916SpIU1NH/ZyMMZwyn+KXL9cYa2A5b7QiLSaN62SbwRXZ6uJ0fvuZLhEc0NN0Xn3KAcB0ZuTzYxJ9+6boZgIpUwAJLU+9FLeHoc0ykJgEaMnw0A39aMkwIaGFkhfiV67ublg2b4bZYEBfdQ1XxzEgprAQ6tV6qMrKINOOfqVLW18bn6xUtVShrW94ke183Xy+9X6OJghFti4HN3rScl6iYjeNfH7ihOFN3tSZNO0zAo+HocNq56ZzArHLcEIM0tVKWjJMSBij5IVcMbfJBMuWCpgNBlgrKwG3mz+mzM/nRljKSiHLzBzV81kcFuwy7uITlhOmEz7H5WI538m2KL0I05OnQyoO4K+yzXTekuT9QFsD4BmhFkIsA9LyzhtRyQeUQZ6qClGBXDKcMbDbMC0ZJiTyUfJCLou7txe9FRUwbzSg98svAefghVyRl8cnLPLs7Es+l91tx762fXyR7cHOgz5FtiKIMD15Ot/Jdnba7MAU2TIGmM6eV0R7AOg5PfL5Ss0I0z5TAal/tiMIRxdbMuytPRnLkmFvIqJT05JhQsggSl7IqHmsVlg+3wpzuQHW7TvAHIPFjoopU/gpIUVOzkWfx+1xo6GrgU9W9rTtGVZkO0E9gZ8Gmq+b7/8iW7eT65VyfqLS3z3y+ZrsIUnKQLM3TVZUTftcaMmwd7fhsS4ZTtcM6fxKS4YJIWNAyQu5KE9/P3q3bYfZYEDvtm1gNht/TJ6Tw42wrNZDMXnyBZ+DMYbT5tM+RbZmh9nnnNSYVD5ZKUov8m+Rrc3MbTrIJyn7uWXK7hFWmoilQGqu72iKLp8rro1g5y8Z9k7nGGnJMCEkBFHyQobx2O2w7tgB80YDLFu3gvX18cdk2dmDCcvUqRcsdGzva+dHVqqN1TBajT7H42XxmKebxzeHm6iZeOVFk4wBlpbBJMVbTNt9cuTz5SrfkRRdAZe4SENwc8UrcP6S4eYeG4wmWjJMCAlf9ClDAAAehwPWnTu5EZaKz+CxDu6RI8vM5Pqw6PVQTp8+YpJhcViw27gb1Uau7f5x03Gf4zKxzKfIdkbyjCsrsnW7uJ2RjQcA477B6Z++zpHPV2eeV59SACSMB8ThPTXhXTLs04o+AEuGvZv70ZJhQkgooOQlijGnE9aqKm6EZcsWeCyD/VKkOh3UZWVQr9ZDWVAwLGFxuB3Y174Plc2VqDZWo76jHm42uMpIBBHykvP4qaDZabMRI425vEDtvdwmhC1DkpS2Q4DLNvxckYQrmk0fkqhoC4C45Mt7bQF5lwxz0ziBWTLMj55olLRkmBASNih5iTLM5UJfTQ3MBgMsn26G2zTYl0SamgpVWRnU+jLEzJoF0ZBRCbfHjYbuBm4aqKUae1r3wOb2TR7Gq8dznWwHmsNdVpGtpXX4aErncQAjXKDl8edtQljALVOWXWaSFESBXjKcrlFym/vRkmFCSASi5CUKMLcbfbtrYTZs5BKWri7+mCQpCarSVVDr9YidOxciCVdIOVKRrem8BmzJymRuj6CB1vvp8emjD8rj5pKS87vRWttGPl+V7jvlo5sJJOaE7LRPoJYMe0dJaMkwISSaUfISoZjHg/69e2E2lMO8qRzu9g7+mESjgWrVKqhX6xE7fz5EUu7XoKO/Y7DItqUaLdYWn+eMk8Vhvnawk+2khEmjm2Zw9HHTPEMTldZ6wNk3/FyRGEiecl6iUgDEp13Rfw9/utiS4ZaBFTq0ZJgQQgKHkpcIwhiDbd++gYRlE1zGwRU+YrUaqpISqPV6xC0sgkgmQ6+jF9tavuBHV471HPN5PqlYilmps/jly/kp+Zcusu1tHz6a0nkUYCOMMshiB6Z9hoympE0H5LH++M9xWS60ZLjFW2cyhiXDCbEy6NS0ZJgQQvyNkpcwxxiD7WA9zOUGWAzlcDY388fEcXFQlayESq9H/KJFcEqAfe37UHXwea6TbcfBYUW2uUm5Pp1sY2UXSCQ8Hm4J8vmJiqVl5PPjUn1rU9ILgaSJgDh4F++RlgwPncahJcOEEBIe6NM1DDHGYG9o4EZYysvhbGrij4liY6Favhzq1XrEXLUIR62nsKmlCtXb3kRta+2wIttsVTa/fHmBbgESlSM0Y3PaBqZ9hiQprQcBR+8I0YmA5ElDRlMKuf9VjX4jxstx/pLhoSt0/L1kOF2jhIqWDBNCiGAoeQkj9qNHYTYYYN5ogOPUKf5xkVKJ+GXLoNKXoWd2DnZ216G6ZSNq3v8/9Nh7fJ4jSZnE16wsTF+IjPgM3xfp6xo+mtLeCAwZoeFJldw0D9/kbWDaRxHv15/bd8nw4PRNIJYMZyQooYmhJcOEEBLKKHkJcfYTJ7lVQuXlsB8drEkRyeWIX7oEWHEVDkxVoLJnL6pb/ohmQ7PP98dKY/lOtkXpRZiSMIW7MDMGdJ8CDn3om6iYz44cSEzSkN4pA6MpyZMByZX9CjHG0N3nHDJa4v8lw+lDak1oyTAhhIQ/Sl5CkKOpCeaNBpjLy2FvaBg8IJMh5qqFaF04GV/k2LHTtBdHu38N7B48RSqWojC1kB9dyU/Jh8zjAdobgFM1gPEfg4mK3Tz8xQFuCfLQ0RRdAbdUeYyjEYwxmG2u4QWwtGSYEELIFaDkJUQ4zp6DpdwAs6Ectvr6wQNSKVxzp+PI7FSUZ3dhd+8uuFglcGrwlNykXL453Bz1RMR2HOeSk50vclNA7Q2AZ4SluxI5t5dP+szB0RTtDECpHlXMl1oy3NLTD6tjhOmmEXiXDA9tRU9LhgkhhIyEkhcBOVtaYC7fBHO5AbZ9+wcPSMQw5Wdj1ww53k1vRof8EPf4QPf+cfHjuGkgzWQs8EiR1HECOLYH+OIVwNQ0/IUAQJkwuMrHW0ybMhWQjFx46u8lw4MjJbRkmBBCyJWh5CXInG1tsJRvgrm8HP179vCPM5EILVOT8PlkOz6b3A9L7GDtSZIiEUWJuSiSJqDIZse49uPA0X8ANtNILwEkZA9M9wxZmqwZx0/78EuGmyw+0zjNPTYYzWNbMqxSSJGeMNCKnpYME0IICQK6qgSBq7MTlk8/hXmjAX27d2Poet0T4xX4fKoTVbkimOK5ZCRGrMTVMToUuSVY2NOOKU2HIXbvG/7EYimQmuezCaE7bQbanMrB6Zw2G5qPmmE07aElw4QQQiICJS8B4uruhmXzZpgNBvRV13BN3QYcyQC+zBOjMk+EbpUbUkgwUxSLhX19KOo2osBuhwxHfZ9QoQbT5qM/ZQY64qbhjGISjrFMnLN4uCXDe71LhitpyTAhhJCIFrLJy7PPPovf//73MBqNKCwsxNNPP40FCxYIHdZFuU0mWLZUwGT4BNbKKoiGLO89pgMqp4tRmStCh0aEqU43ruvrRZHRhnk2O2KHDIXYYtNhjJuGJvkkNGAC9jiysL9XjdbjDjiOeJ+zH4BvO3+viy0ZzhjYR4eWDBNCCAlXIZm8vPXWW1i3bh2ef/55FBUV4U9/+hNKS0vR2NiItLTQ2aAPANy9vTBv2QLjh/+Fp2YPxC4uuRABOKnlRliqckWQxrux0NaHn/TbsOC0DckeD9yQ4Jw0C19IuARlnysbhz3Z6LGpgK7zX4nrjHuhJcPeFTq0ZJgQQkikEzE2muqH4CoqKsL8+fPxzDPPAAA8Hg+ysrLwwAMP4JFHHrno95rNZmg0GphMJqjVo1vyO1YeqxWnN/4XbR+8g9i645C6Bv8TNqVyCUv9VA8mxNix0GZDUb8NiU4ZDrNs1Hsm4BAbj0Oe8TjKxsEOuc9zn79kOF2j5JISWjJMCCEkgo3l+h1yIy8OhwO1tbVYv349/5hYLEZJSQkqKysFi+vMyXpUvvIbxOw9jOzj/ZC7AO9/2nNJwK5cwDLRiWmxNlzTr8Bi0zg09ExAhWc8nmbj0cTSoIlV8IWvsxKU0GtoyTAhhBAyViGXvHR0dMDtdkOr9d3IT6vVomFot9kBdrsddrud/7fZfIGusVfo2GfvouDNwaXNxgTg+FQPrNkSMKUWEmcuPPJpqFHl4fD4dH7J8GxaMkwIIYT4VdhfTTds2IDHH3884K8z88YfYverb6ArMw79BdORPPOrmJo9D7qUJFoyTAghhARRyCUvKSkpkEgkaG1t9Xm8tbUVOp1u2Pnr16/HunXr+H+bzWZkZWX5Pa7kxGSUfn7I789LCCGEkLEJucpPuVyOuXPnoqKign/M4/GgoqICxcXFw85XKBRQq9U+X4QQQgiJXCE38gIA69atw5133ol58+ZhwYIF+NOf/gSr1Yq77rpL6NAIIYQQIrCQTF5uueUWtLe349FHH4XRaMSsWbNQXl4+rIiXEEIIIdEnJPu8XIlg9HkhhBBCiH+FdZ+XK+XNxQK1ZJoQQggh/ue9bo9mTCXikheLxQIAAVlxRAghhJDAslgs0Gg0Fz0n4qaNPB4PmpuboVKp/L4jsncZ9pkzZ2hKKgTQ+xFa6P0ILfR+hB56Ty6OMQaLxYKMjAyIxRdfDB1xIy9isRjjxo0L6GvQkuzQQu9HaKH3I7TQ+xF66D25sEuNuHiFXJ8XQgghhJCLoeSFEEIIIWGFkpcxUCgUeOyxx6BQKIQOhYDej1BD70doofcj9NB74j8RV7BLCCGEkMhGIy+EEEIICSuUvBBCCCEkrFDyQgghhJCwQskLIYQQQsIKJS+j9Oyzz2LChAlQKpUoKipCTU2N0CFFrQ0bNmD+/PlQqVRIS0vDDTfcgMbGRqHDIgN++9vfQiQSYe3atUKHErXOnTuHb33rW0hOTkZMTAwKCgqwe/duocOKSm63Gz//+c+Rk5ODmJgYTJo0Cb/85S9HtX8PuTBKXkbhrbfewrp16/DYY49hz549KCwsRGlpKdra2oQOLSpt27YNa9asQVVVFTZv3gyn04lVq1bBarUKHVrU27VrF1544QXMnDlT6FCiVnd3N6666irIZDIYDAYcOnQIf/jDH5CYmCh0aFHpd7/7HZ577jk888wzOHz4MH73u9/hiSeewNNPPy10aGGNlkqPQlFREebPn49nnnkGALd/UlZWFh544AE88sgjAkdH2tvbkZaWhm3btmHJkiVChxO1ent7MWfOHPz1r3/Fr371K8yaNQt/+tOfhA4r6jzyyCPYuXMnduzYIXQoBMBXvvIVaLVa/OMf/+Afu+mmmxATE4NXX31VwMjCG428XILD4UBtbS1KSkr4x8RiMUpKSlBZWSlgZMTLZDIBAJKSkgSOJLqtWbMG1157rc/fCgm+Dz/8EPPmzcPNN9+MtLQ0zJ49G3/729+EDitqLVq0CBUVFThy5AgAYN++ffjiiy+g1+sFjiy8RdzGjP7W0dEBt9sNrVbr87hWq0VDQ4NAUREvj8eDtWvX4qqrrkJ+fr7Q4UStN998E3v27MGuXbuEDiXqnThxAs899xzWrVuH//3f/8WuXbvwP//zP5DL5bjzzjuFDi/qPPLIIzCbzcjNzYVEIoHb7cavf/1r3H777UKHFtYoeSFhbc2aNTh48CC++OILoUOJWmfOnMGDDz6IzZs3Q6lUCh1O1PN4PJg3bx5+85vfAABmz56NgwcP4vnnn6fkRQBvv/02XnvtNbz++uuYMWMG6urqsHbtWmRkZND7cQUoebmElJQUSCQStLa2+jze2toKnU4nUFQEAO6//358/PHH2L59O8aNGyd0OFGrtrYWbW1tmDNnDv+Y2+3G9u3b8cwzz8But0MikQgYYXRJT0/H9OnTfR7Ly8vDf//7X4Eiim4//vGP8cgjj+DWW28FABQUFOD06dPYsGEDJS9XgGpeLkEul2Pu3LmoqKjgH/N4PKioqEBxcbGAkUUvxhjuv/9+vPfee/jss8+Qk5MjdEhRbeXKlThw4ADq6ur4r3nz5uH2229HXV0dJS5BdtVVVw1rHXDkyBGMHz9eoIiiW19fH8Ri30utRCKBx+MRKKLIQCMvo7Bu3TrceeedmDdvHhYsWIA//elPsFqtuOuuu4QOLSqtWbMGr7/+Oj744AOoVCoYjUYAgEajQUxMjMDRRR+VSjWs3iguLg7JyclUhySAhx56CIsWLcJvfvMbfOMb30BNTQ1efPFFvPjii0KHFpWuu+46/PrXv0Z2djZmzJiBvXv34o9//CO++93vCh1aeGNkVJ5++mmWnZ3N5HI5W7BgAauqqhI6pKgFYMSvl156SejQyIClS5eyBx98UOgwotZHH33E8vPzmUKhYLm5uezFF18UOqSoZTab2YMPPsiys7OZUqlkEydOZD/72c+Y3W4XOrSwRn1eCCGEEBJWqOaFEEIIIWGFkhdCCCGEhBVKXgghhBASVih5IYQQQkhYoeSFEEIIIWGFkhdCCCGEhBVKXgghhBASVih5IYQQQkhYoeSFEEIIIWGFkhdCCCGEhBVKXgghhBASVih5IYQQQkhY+f8faWci5Jcj6gAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.linspace(-10,10,100)\n",
    "y = np.sin(x)\n",
    "\n",
    "plt.subplots(2,1)\n",
    "\n",
    "plt.subplot(2,1,1)\n",
    "plt.plot(x,y)\n",
    "\n",
    "plt.subplot(2,1,2)\n",
    "x1 = np.arange(10)\n",
    "y1 = 1.5 * x1\n",
    "y2 = 2.5 * x1\n",
    "y3 = 3.5 * x1\n",
    "y4 = 4.5 * x1\n",
    "plt.plot(x1,y1,x1,y2,x1,y3,x1,y4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.arange(10)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.6"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "d44d76ef8cbbc4331cecfe2e59228ac31ebb71026289858a116838be7168b60b"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
